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IBCESS

1st INTERNATIONAL BLACK SEA CONGRESS ON ENVIRONMENTAL SCIENCES (1st IBCESS)

FULL PAPER BOOK August 31-September 03, 2016

ISBN: 978-975-01408-9-1

IBCESS

1st INTERNATIONAL BLACK SEA CONGRESS ON ENVIRONMENTAL SCIENCES (IBCESS) Giresun, Turkey • August 31 - September 03, 2016

TABLE OF CONTENTS - FULL PAPER...........................................................................................PAGE NUMBER RHODOCOCCUS RUBER DRY BIOMASS AS A NEW SOLID PHASE EXTRACTOR FOR PRECONCENTRATION AND/OR SEPARATION OF CD(II) IONS IN VARIOUS WATER SAMPLES Esin Kiray, Ergin Kariptas, Mehmet Yetis, Cigdem Er and Harun Ciftci.........................................................................1 TEMPORAL VARIATIONS OF EASTERN BLACK SEA AEROSOL İlker Balcılar, Abdullah Zararsız, Yakup Kalaycı, Güray Doğan and Gürdal Tuncel...................................................................................................................................................................................................................9 REGRESSION MODELLING OF HOURLY OZONE CONCENTRATION IN GIRESUN Yılmaz YILDIRIM and Eren KARAKAVUZ..........................................................................................................................................21 EVALUATION OF LAND LOSS FOR ENVIROMENTAL FACTS: THE ATASU DAM EXAMPLE Osman Tuğrul BAKİ, Egemen ARAS and Banu YILMAZ.......................................................................................................31 3D SPATIAL DISTRIBUTION OF WATER QUALITY PARAMETERS IN KARACAÖREN-II DAM RESERVOIR Firdes Yenilmez.............................................................................................................................................................................................................43 COMPARISON OF SEX AND SIZE STRUCTURE OF CAPOETA TRUTTA POPULATIONS IN ATATURK AND KARAKAYA DAM LAKES Ayse Gul SAHIN, Unal ISPIR and Rıdvan TEPE................................................................................................................................50 APPORTIONMENT OF POLLUTION SOURCES OF SAKARYA RIVER USING MULTIVARIATE STATISTICAL TECHNIQUES Rabia KOKLU.................................................................................................................................................................................................................56 THE DETECTION MICROBIOLOGYCAL QUALITY GROUND WATER IN SIVAS Özlem Pelin CAN.......................................................................................................................................................................................................65 RECLAMATION OF GREY WATER USING ELECTROCOAGULATION PROCESS Yasemin Çalışkan, Hülya Öztürk, Nihal Bektaş and H. Cengiz Yatmaz.......................................................................70 THE REUSE OF TEXTILE WASTEWATER IN DISPERSE DYEING PROCESSIN THE LIGHT OF ECOLOGY AND ECONOMY Gül Kaykıoğlu, Rıza Atav, Yalçın Güneş and Elçin Güneş.......................................................................................................83

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TREATMENT ALTERNATIVES OF LANDFILL LEACHATE Melike YALILI KILIÇ..................................................................................................................................................................................................92

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MOBILE SOLID WASTE INCINERATION PROJECT FOR THE CASE STUDY OF ŞIRNAK - TRASH, ANIMAL AND AGRICULTURAL WASTE-MOBILE CO-INCINERATION Yıldırım İsmail TOSUN.......................................................................................................................................................................................102 USE OF BIO WASTE ACTIVE CARBON-ALKALI PELLETS IN FLUIDIZED BED COMBUSTION CHAMBERS FOR EMISSION CONTROL Yıldırım İsmail TOSUN.......................................................................................................................................................................................117


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ANTIOXIDANT ACITIVITY OF SOME GREEN ALGAE Tünay Karan and Ramazan Erenler.........................................................................................................................................................133 AMMONIA EMISSIONS IN FOUR TURKISH SHEEP BARNS IN AUTUMN SEASON Ilker Kilic and Nesli Kocaalili..........................................................................................................................................................................139 SEED PRIMING TO OVERCOME EXTERNAL STRESS CONDITIONS UNDER CHANGING ENVIRONMENT Muhittin KULAK.....................................................................................................................................................................................................147 THE INVESTIGATION OF POSSIBILITY OF FLOODING AND PEAK FLOWS IN SORGUN BASIN AND ITS SUB BASINS USING GEOGRAPHIC INFORMATION SYSTEM Ümit Yıldırım and Cüneyt Güler..............................................................................................................................................................153 PHYSICOCHEMICAL ANALYSIS OF WATER QUALITY OF BROOK TEKELIIÇI Ekrem Mutlu, Telat Yanık and Nicoleta Anca SUTAN...........................................................................................................160 BIOPLASTIC WASTE MANAGEMENT Ezgi Bezirhan Arikan and Havva Duygu Ozsoy............................................................................................................................171 IMPLEMENTATON OF ISO 14001 IN HEALTH SERVICE SECTOR AND WASTE MANAGEMENT Asude Ateş and Hülya Demirel..................................................................................................................................................................180 ECOTOXICOLOGICAL PRACTICES OF ENVIRONMENT SEDIMENTOLOGY Arife ŞİMŞEK and Gülfem BAKAN..........................................................................................................................................................188 REMOVAL OF MANGANESE (II) IONS FROM AQUEOUS SOLUTIONS BY ADSORPTION ON CARBONIZED WALNUT SHELL Bircan Köse and Saliha Erentürk................................................................................................................................................................200 UNIVERSITY STUDENTS’ PREFERENCES FOR DRINKING WATER AT THEIR HOMES AND DORMITORIES Cemile Dede, Nursan Cinar and Tijen Nemut..............................................................................................................................211 PACKAGING MATERIALS USED IN FOODSTUFFS AND ENVIRONMENTAL HEALTH Duygu BALPETEK KULCU..............................................................................................................................................................................217

PREPARATION OF ADSORBENTS FROM HAZELNUT SHELLS AND APRICOT SEED SHELLS AND THEIR ADSORPTION BEHAVIORS FOR THE REMOVAL OF Cu(II) Bircan Köse and Saliha Erentürk................................................................................................................................................................228 REMOVAL OF MICROPOLLUTANTS IN WATER WITH ADVANCED TREATMENT PROCESSES Sevde USTUN ODABASI and Hanife BUYUKGUNGOR....................................................................................................239

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METAL LEVELS IN SEDIMENTS FROM THE AREA WHERE EFFLUENTS OF WWTP OF ELAZIĞ DISCHARGING INTO THE KEBAN DAM LAKE Memet Varol and Muhammet Raşit Sünbül.................................................................................................................................224

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SYNTHESIS AND CHARACTERIZATION OF SILICA BASED ACIDIC CATALYSTS WITH THE IMPREGNATION METHODS Veli SIMSEK, Zerrin PAT and Kirali MURTEZAOGLU............................................................................................................247 ENVIRONMENTAL IMPACTS OF DESALINATION PLANT INTAKES AND DISCHARGES AND HYDRAULIC PLANNING Mehmet Berkün and Ümmükülsüm Özel Akdemir...............................................................................................................257 STREAM BANK SOIL LOSSES FROM SEMIARID SUB-WATERSHED Mustafa TUFEKCIOGLU..................................................................................................................................................................................267 CHEMICAL OXYGEN DEMAND (COD) REMOVAL FROM WASTEWATER BY USING FLY ASH OF POWER PLANTS Bünyamin Şengül and Ümit Şengül........................................................................................................................................................275 DISTRIBUTIONS AND AIR-SOIL EXCHANGE OF PAHS AND PCBS IN THE ATMOSPHERE OF ISTANBUL Banu Çetin, Fatma Öztürk, Melek Keleş and Sema Yurdakul..........................................................................................289 PAH DETERMINATIONS BY THE PASSIVE AIR SAMPLER AND PINE COMPONENTS IN BURSA Nihan Durak, Fatma Esen, A.Egemen Sakin and Yücel Taşdemir................................................................................299 RISK ESTIMATION OF HALOGENATED POPS IN INDOOR DUST IN AN INDUSTRIALIZED CITY M. Civan, M. Kara and Bilgehan Basaran............................................................................................................................................309 POLYCHLORINATED BIPHENYLS (PCBS) LEVELS IN INDOOR DUST Merve Kara, Bilgehan Basaran and Mihriban Civan.................................................................................................................318 OLEANDER (NERIUM OLEANDER L.) SEED AS A SOURCE FOR FUNGAL AEROSOLS Adem IMALI and Ferudun KOCER........................................................................................................................................................329 ARTVIN (CITY CENTER) INTEGRATED SOLID WASTE MANAGEMENT Pelin ARAS and Ayşe KULEYİN..................................................................................................................................................................335 SELECTIVE SPECTROPHOTOMETRIC DETERMINATION OF TRACE COPPER (II) ENVIRONMENTAL WATER SAMPLES Berrin TOPUZ and Gizem OKUR............................................................................................................................................................345

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TREATMENT OF SUNSET YELLOW FCF DYE BY UV/K2S2O8 PROCESS Sevil ÇALIŞKAN ELEREN and Ebru Garip..........................................................................................................................................358

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MASS BALANCE FOR NITROGEN AND PHOSPHORUS LOADS IN LAKE SAPANCA Seda TUNAY, Bulent SENGORUR and Rabia KOKLU...........................................................................................................368 COLOR REMOVAL FROM WASTEWATER BY USING TWO-STEP (BIOLOGICAL AND CHEMICAL) AEROBIC FILTER REACTORS Yağmur Uysal and Mehmet Bilgiç...........................................................................................................................................................377


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OLIVE OIL PROCESSING: FROM ENVIRONMENTAL RISK TO BENEFICIAL SUBSTANCES Evren Altiok..................................................................................................................................................................................................................389 REMOVAL OF NICKEL FROM INDUSTRIAL WASTEWATER BY ELECTROCOAGULATION-ULTRAFILTRATION PROCESS M. Dönmez Öztel and F. Akbal...................................................................................................................................................................402 DATA-DRIVEN SIMULATIONS OF STREAM METABOLISM USING DIEL OXYGEN TECHNIQUE Miraç ERYİĞİT, Nusret KARAKAYA and Fatih EVRENDİLEK..........................................................................................410 APPLICATION OF FENTON REAGENT AND ADSORPTION AS ADVANCED TREATMENT PROCESSES FOR REMOVAL OF MAXILON RED GRL Fehiman Çiner............................................................................................................................................................................................................423 DROUGHT AS AN ENVIRONMENTAL PROBLEM Alaeddin BOBAT.....................................................................................................................................................................................................432 BIOSORPTION OF AZO DYE ON TO WASTE SLUDGE M. Sarioglu (Cebeci) and M. Aşkal..........................................................................................................................................................448 OPTIMIZING DYE ADSORPTION USING COTTONSEED CAKE, ULTRASOUND, BOX-BEHNKEN, NEURAL NETWORKS AND REGRESSIONS Musa Buyukada, Fatih Evrendilek and Nusret Karakaya......................................................................................................463 IMPLEMENTATON OF ISO 14001 IN HEALTH SERVICE SECTOR AND WASTE MANAGEMENT Asude Ateş and Hülya Demirel..................................................................................................................................................................475 THE EFFECTS ON MISUSE OF AGRICULTURAL LANDS ON ENVIRONMENT Erdal DAGISTAN, Aybuke KAYA and Dilek BOSTAN BUDAK......................................................................................483 ENVIRONMENTAL POLLUTION FROM HYDROCARBURES IN GJANICA RIVER, IN PATOS-MARINEZ REGION Alma Shehu, Seit Shallari, Alfred Mullaj and Marianithi Guri.........................................................................................492 ANTIOXIDANT, ANTIBACTERIAL, ANTITYROSINASE ACTIVITIES AND ATRANORIN CONTENTS OF SOME CLADONIA SPECIES Kadir KINALIOĞLU, Aytaç GÜDER and Sinem AYDIN.......................................................................................................500

HEPATOPROTECTIVE POTENTIAL OF BORIC ACID, ORAX, COLEMANITE AND ULEXITE AGAINST 2,3,7,8-TETRACHLORODIBENZO-P-DIOXIN IN CULTURED RAT HEPATOCYTES Hasan Türkez...............................................................................................................................................................................................................521 THE GENO-PROTECTIVE EFFECT OF PROPOLIS ON ALUMINUM SULPHATE-INDUCED DNA DAMAGE IN HUMAN LYMPHOCYTES Hasan Türkez...............................................................................................................................................................................................................527

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THE HISTOPATHOLOGICAL EFFECTS OF WATER POLLUTION ON MARSH FROGS (PELOPHYLAX RIDIBUNDUS) LIVING AROUND KARASU RIVER, TURKEY Turgay Şişman, Suat Çolak and Ümit İncekara.............................................................................................................................511

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ECOLOGICAL EVALUATIONS ON RAPID HABITAT LOSSES OF GIRESUN ISLAND (ARETIAS) Ümit İncekara.............................................................................................................................................................................................................534 DESIGN AND IMPLEMENTATION OF A SMART D-STATCOM IN SMALL SCALE WIND TURBINES Yanmaz, K., Mengi, O., Ö. and Altaş, İ., H............................................................................................................................................541 BACTERIAL BIO-PLASTIC PRODUCTION AND USE OF POSSIBILITIES Selin KALKAN............................................................................................................................................................................................................552 THE İNVESTIGATION COLIFORMS AND E. COLI IN DRINKING AND USING WATERS OF KONYA AND REGION Tufan AKYÜZ and Emine ARSLAN........................................................................................................................................................563 EVALUATION OF CONTROL MONITORING RESULTS IN TERMS OF PUBLIC HEALTH OF CLOSTRIDIUM PERFRINGES IN DRINKING AND USING WATERS IN KONYA AND DISTRICS Tufan AKYÜZ and Emine ARSLAN........................................................................................................................................................569 ANTIOXIDANT, ANTIBACTERIALAND ANTI-UREASE ACTIVITY OF FLAVOPARMELIA CAPERATA AND XANTHOPARMELIA STENOPHYLLA LICHENS Bahar BİLGİN SÖKMEN, Kadir KINALIOĞLU and Sinem AYDIN..............................................................................574 RENEWABLE ENERGY SYSTEMS, ENVIRONMENT EFFECTS, AN ESTIMATED DESIGN OF WIND TURBINE WITH SOLAR PANELS Necla Çağlarırmak and Fatih Burçin Gürarslan............................................................................................................................585 MEDIA CAN WARN PEOPLE ON ENVIRONMENTAL DANGERS: WARNING PRODUCTIONS Prof. Dr. Sedat Cereci............................................................................................................................................................................................602 EFFECT OF TIO2 AND ZnO NANOPARTICLES ON BARLEY PLANT Zeynep Gorkem Dogaroglu and Nurcan Koleli..........................................................................................................................613 PET WATER BOTTLE: A CARBON FOOTPRINT ASSESSMENT Sevde USTUN ODABASI and Hanife BUYUKGUNGOR....................................................................................................623 SLAUGHTERHOUSE PRODUCTS AND ENVIRONMENTAL IMPACT Duygu BALPETEK KULCU and Umit GURBUZ..........................................................................................................................629

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EXAMPLE USING DIFFERENT METHODS AND TECHNIQUES OF TEACHING ENVIRONMENTAL PROBLEMS Lütfiye ÖZALEMDAR.........................................................................................................................................................................................636

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ENERGY PRODUCTION FROM ORGANIC WASTE Aysun Altikat, Sevtap Doğru, Yusuf Alparslan Argun and Züleyha Bingul...........................................................................................................................................................................................................649 METHYLENE BLUE ADSORPTION ONTO HAZELNUT SHELL ACTIVATED CARBON PREPARED BY HYDROTHERMAL CARBONIZATION AND CHEMICAL ACTIVATION Murat KILIÇ..................................................................................................................................................................................................................660


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HYDROTHERMAL AND ACID PRETREATMENT OF WASTE BIOMASS TO ENHANCE THE CHARACTERISTICS OF PYROLYSIS PRODUCTS Murat KILIÇ and Başak Burcu UZUN...................................................................................................................................................670 CATALYTIC UPGRADING OF FAST PYROLYSIS BIOMASS VAPORS OVER COBALT PROMOTED ZSM-5 CATALYST Esin APAYDIN-VAROL, Murat KILIÇ, Elif SARAÇOĞLU and Başak Burcu UZUN......................................678 PYROLYSIS KINETICS AND THERMOGRAVIMETRIC CHARACTERISTICS OF CRUDE OIL SLUDGE USING TG-FTIR-MS Murat KILIÇ, Gamzenur ÖZSİN, Ersan PÜTÜN, Esin APAYDIN VAROL and AYŞE E. PÜTÜN........688 BIOREMOVAL OF HEAVY METAL IONS FROM AQUEOUS SOLUTIONS ONTO HAZELNUT HUSK Murat KILIÇ, Elif SARAÇOĞLU and Esin APAYDIN VAROL...........................................................................................694 THERMAL DEGRADATION AND PYROLYSIS BEHAVIOR OF BREWED TEA WASTE BY TG-FTIRMS: KINETICS AND EVOLVED GAS ANALYSIS Murat KILIÇ, Gamzenur ÖZSİN, ELIF SARAÇOĞLU and Esin APAYDIN VAROL.......................................701 ESTIMATION OF DAILY SUSPENDED SEDIMENT LOAD WITH AN ARTIFICIAL NEURAL NETWORK Banu Yılmaz, Egemen ARAS and Sinan NACAR........................................................................................................................708 POLYCHLORINATED BIPHENYLS (PCBS) LEVELS IN INDOOR DUST Merve Kara, Bilgehan Basaran and Mihriban Civan.................................................................................................................720 RISK ESTIMATION OF HALOGENATED POPS IN INDOOR DUST IN AN INDUSTRIALIZED CITY M. Civan, M. Kara and Bilgehan Basaran............................................................................................................................................729 TITANIUM DIOXIDE USAGE IN ROAD PAVEMENTS AS POLLUTION REDUCER Erol İSKENDER, Atakan AKSOY, Cansu İSKENDER and Aytuna SAYIN.................................................................738 CLIMATE CHANGE AND AGRICULTURE: THREATS AND WAY OUT Ufuk GÜLTEKİN and Tuğçe UĞUR........................................................................................................................................................749

IDENTIFICATION AND SOURCE APPORTIONMENT OF TRACE ELEMENTS IN SUBURBAN AREA OF ANKARA İlke Çelik, Tayebeh Goli, Seda Aslan, İpek İmamoglu and Gurdal Tuncel.............................................................765 REMOVAL OF METHYL ORANGE IN AQUEOUS SOLUTION BY FENTON/ ULTRASONIC FENTON/ ELECTRO-FENTON OXIDATION Gamze Koyuncu Türkay, Habibe Elif Gülşen, Ceyhun Akarsu, Ümit Elyiğit and Halil Kumbur....................................................................................................................................................................775

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A NUMERICAL INVESTIGATION OF FLUE GAS TEMPERATURE EFFECT OF NUCLEAR POWER PLANT’S COOLING TOWER TO ENVIRONMENT TEMPERATURE Emre Aşkın Elibol and Ferdi Özbilgin....................................................................................................................................................758

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NEED OF CLEAN AND SUSTAINABLE ENERGY SYSTEMS IN AGRICULTURE Kasım Eren Tuna and Dilek Bostan Budak........................................................................................................................................785 MONITORING OF SEASONAL ORGANIC AND INORGANIC POLLUTION AT THE MID-BLACK SEA COAST OF TURKEY Sevde ÜSTÜN ODABAŞI, Bareera MARYAM, İlknur ŞENTÜRK, Feryal AKBAL, Gülfem BAKAN and Hanife BÜYÜKGÜNGÖR.....................................................................................................................................................................793 SPATIAL AND SEASONAL CHARACTERISTICS OF INORGANIC CHEMICALS IN ARMAĞANKÖY DAM WATER, THRACE REGION Füsun Ekmekyapar and Ahmet Serhat Akar..................................................................................................................................802 INVESTIGATION OF SPATIAL AND TEMPORAL DISTRIBUTIONS OF PAHS IN THE ATMOSPHERE OF DILOVASI Banu Çetin, Işıl Çelik, Cevdet Doğan, Melek Keleş, Sema Yurdakul and Fatma Öztürk...........................814 LEVELS OF POLYCYCLIC AROMATIC HYDROCARBON (PAH) CONCENTRATIONS IN SURFACE SOILS, BURSA: SUMMER SEASON Gizem Eker and Melis Hatipoğlu...............................................................................................................................................................821 EMISSION INVENTORY OF SHIPS IN SAMSUN PORT, TURKEY Fatih ALVER, Betül SARAÇ and Ülkü ALVER ŞAHİN..............................................................................................................832 NEGATIVE EFFECT OF E-WASTE ON ENVIRONMENTAL HEALTH AND RECYCLING Dogru S., Argun Y.A., Bingul Z. and Altikat A................................................................................................................................842 AN INVESTIGATION INTO THE USE OF SCRAP TIRES IN SOIL IMPROVEMENT APPLICATIONS Ertuğrul ORDU, Perihan BİÇER, Şeyma ORDU and Emine G. ABANOZOĞLU............................................854 SOURCE IDENTIFICATION OF VOCS IN METU CAMPUS THROUGH FACTOR ANALYSIS Elif Sena Uzunpınar, Ezgi Sert, Seda Aslan Kılavuz, İpek İmamoğlu and Gürdal Tuncel..........................862 ENVIRONMENTAL IMPACT ASSESSMENT OF DAIRY SECTOR Züleyha Bingül, Aysun Altıkat, Sevtap Doğru and Yusuf Alparslan Argun.........................................................873 MODELING OF PM10 DISPERSION IN RIZE CITY CENTER Nilay AKÇAY, Özgür ZEYDAN, Murat KARAYILAN, Ülkü ALVER ŞAHİN, Fatih ALVER and Burcu ONAT...................................................................................................................................................................880

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LONG TERM VARIATION OF PM10 AND SO2 IN THE ATMOSPHERE OF GIRESUN, ORDU AND SAMSUN CITY IN TURKEY Ülkü ALVER ŞAHİN, Burcu UZUN, Özcan AKIN, Burcu ONAT, Fatih ALVER and Nihat TAŞ..........891

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OPTIMIZATION OF SEPARATION PARAMETERS OF NICKEL (II) IONS ON ACTIVATED CARBON FROM VINE SHOOTS Cigdem Er, Harun Ciftci, Esin Kiray, Ergin Kariptas, Mehmet Yetis and Mehmet Erdem........................901 DETERMINATION OF SOME ANIONS IN HERBAL TEA BY CAPILLARY ELECTROPHORESIS Behice YAVUZ ERDOĞAN and A. Nur ONAR...........................................................................................................................906


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DETERMINATION OF ELEMENTAL COMPOSITION OF WINTER SEASON PARTICULATES IN ANTALYA URBAN ATMOSPHERE Ahmet Mustafa Tepe, İlker Balcılar and Güray Doğan..........................................................................................................912 TEMPORAL TRENDS OF ATMOSPHERIC POLLUTANTS IN ISTANBUL ATMOSPHERE Sema Yurdakul, Banu Çetin and Fatma Öztürk...........................................................................................................................921 BIOPLASTIC AS A NEW GENERATION BIOMATERIAL H. Duygu OZSOY and Selin SARICA....................................................................................................................................................930 FRESHWATER MULTISTATISTICS: FACTOR ANALYSIS IN PORSUK STREAM BASIN (TURKEY) Cem TOKATLI, Esengül KÖSE, Özgür EMİROĞLU and Arzu ÇİÇEK.......................................................................937 VERTICAL GARDENS TO CREATE NATURAL EFFECTS IN INDOOR LANDSCAPES Nermin BAŞARAN and Engin EROĞLU............................................................................................................................................944 SUSPENDED SOLID INDICATOR” BASED MEMBRANE FOULING MODELING Turgay Dere...................................................................................................................................................................................................................958 MONITORING THE CHANGES OF TEMPORAL AND REGIONAL PAH LEVELS BY OLIVE SAMPLES Betül Yıldırım, Fatma Esen and Yücel Taşdemir..........................................................................................................................968 THE EFFECTS ON MISUSE OF AGRICULTURAL LANDS ON ENVIRONMENT Erdal DAGISTAN, Aybuke KAYA and Dilek BOSTAN BUDAK......................................................................................979 PARENT’S KNOWLEDGE, ATTITUDES AND PRACTICES TO PROTECT THEIR CHILDREN FROM SECONDHAND AND THIRDHAND TOBACCO SMOKE Cemile Dede, Nursan Cinar, Dilek Menekse and Engin Menekse...............................................................................989 GREENHOUSE GAS EMISSIONS FROM ENERGY SECTOR IN THE TURKEY Aytuğ TEKBAŞ, Mesut TEKBAŞ and Nihal BEKTAŞ.................................................................................................................999 PERCEPTION OF WORKERS ON ENVIRONMENTALLY SOUND CHEMICAL APPLICATION FOR GREENHOUSE PRACTICES İbrahim Alpay Sakartepe, Çiğdem Kıvılcımdan Moral and Kadir Gedik............................................................1006

ASSESMENT OF SOME METAL BIOACCUMULATION IN TISSUES OF KAPWAETI (CAPOETA UMBLA HECKEL, 1843) FROM KARASU RIVER Turgay Şişman and Mucip Genişel.......................................................................................................................................................1024 ASSESSMENT OF POINT SOURCE POLLUTION IMPACT FROM SBR WASTEWATER TREATMENT PLANT ON THE RECEIVING BODY Başak K. TAŞELİ......................................................................................................................................................................................................1032

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GREEN MARKETING PRACTICES AT THE HOSPITALITY BUSINESSES: NEW JASMİN HOTEL SAMPLE Salih MEMİŞ and Hakan BENEK ..........................................................................................................................................................1014

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ANTIPROLIFEATIVE ACITIVITY OF HERACLEUM PLATYTAENIUM BOISS Ramazan Erenler...................................................................................................................................................................................................1043 A STUDY ON BIOCATALYTIC HYDROLYSIS OF WASTE EDIBLE OIL Fatma Güler, Neşe Karasungur, Togayhan Kutluk, Başar Uyar and Nurcan Kapucu......................................................................................................................................................................................................1050 ORGANIC SOLVENT AND TEMPERATURE TOLERANCE OF LIPASE FOR FAME SYNTHESIS FROM MICROALGAE OIL Togayhan Kutluk and Nurcan Kapucu.............................................................................................................................................1055

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ANTIBIOTICS RESISTANCE AND VIRULENCE FACTORS OF PSEUDOMONAS AERUGINOSA ISOLATED FROM PETROLEUM OIL CONTAMINATED SLUDGE Belgin ERDEM and Zeynep KARAKAŞ............................................................................................................................................1060

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Full Papers

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RHODOCOCCUS RUBER DRY BIOMASS AS A NEW SOLID PHASE EXTRACTOR FOR PRECONCENTRATION AND/OR SEPARATION OF Cd(II) IONS IN VARIOUS WATER SAMPLES Esin Kiray1, Ergin Kariptas2, Mehmet Yetis3, Cigdem Er4 and Harun Ciftci5 Ahi Evran University, Faculty of Science and Arts, Department of Biology, Kirsehir, Turkey Ahi Evran University, Faculty of Medicine, Department of Microbiology, Kirsehir, Turkey [email protected] 3 Ahi Evran University, Faculty of Medicine, Kirsehir, Turkey 4 Ahi Evran University, Mucur Vocational Training School, Kirsehir, Turkey 5 Ahi Evran University, Faculty of Medicine, Department of Biochemistry, Kirsehir, Turkey 1 2

In this study, Rhodococcus ruber dry biomass (RrDB) was used as a biosorbent extractant for preconcentration of trace Cd(II) previous to measurement by flame atomic absorpiton spectrometry (FAAS). R. ruber is important in many biotransformations and some transformations results in useful commercial processes. Another important application of Rhodococcus comes from bioconversion, using biological systems to convert cheap starting material into more valuable compounds, such as its ability to metabolize harmful environmental pollutants, including toluene, naphthalene, and herbicides. Therefore, these organisms have environmental, commercial and economical aspects major importance. In present study, we investigated parameters bio adsorption of in various water samples. The experimental parameters that affected the extraction efficiency of the method such as pH, flow rate and volume of the sample solution, concentration of eluent, amount of biosorbent, and effect of common matrix ions were investigated and optimized. A high preconcentration factor of Cd(II) 150 was obtained. The quantitative recovery (above 95 %) of cadmium ions was obtained at pH 6.5-8.0. Some analytical parameters such as limit of detection (LOD) and linear dynamic range of the method were obtained. The LOD for Cd(II) was calculated as 0.86 µg L-1. The accuracy of the method was verified by analysis of a certified standard reference material. The used procedure was applied to the definition of the analytes in various water samples with convincing results.

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ABSTRACT

Keywords: Biomass, cadmium, FAAS, Rhodococcus ruber, SPE

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INTRODUCTION In recent years, pollution of the environment by heavy metals has received considerable attention. Among heavy metals, Cd not only cause environmental pollution, but also bring harm to people’s health (Ezoddin, 2010; Silva, 2009). Cadmium is one of the most hazardous elements to human health, because it can cause adverse effects on metabolic processes of human beings (Gama, 2006). Cadmium is highly toxic even at low concentrations, causing damages to organs such as the kidneys, liver, and lungs (Maranhão, 2005). One of the main pathways that cadmium enters into the human body is through the intake of food and drinking water. Therefore, monitoring of cadmium concentrations in food and water samples is important (Mehdinia, 2015). Flame atomic absorption spectrometry (FAAS) has been widely selected and used as the technique owing to its high sensitivity, simplicity, reproducibility, wide dynamic concentration rangem and its low cost at these determinations (Ezer, 2009; Soylak, 2010). But the sensitivity and selectivity of FAAS is usually insufficient for the determination of heavy metals at trace concentration in complex matrix environmental samples In the trace analysis, therefore, preconcentration or separation of trace elements from the matrix is frequently necessary in order to improve their detection and selectivity by FAAS (Yildiz, 2013). There are various separation methods used for this purpose, with the most widely used being solid-phase extraction (Saçmaci, 2012), cloud point isolation (Pytlakowska, 2013), ion Exchange (Anthemidis, 2012) solvent extraction (Meng, 2014), and electrodeposition (Morales, 2005). But the solid phase extraction (SPE) has been increasingly used for preconcentration and separation of trace and ultra trace amounts of inorganic and organic species from complex matrices (Someda, 2006). These include higher enrichment factors, absence of emulsion and safety with respect to hazardous samples, minimal costs due to low consumption of reagents, flexibility, ease of automation (Amin, 2012).

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Biosorption is the adsorbtion and removal of particulates, metals or metalloids, and compounds from solution by biomaterials. Significant amounts of metals can be accumulated by different types of procedures that are dependent and independent of metabolism (Saçmacı, 2014). Biomass of bacteria, algae, fungi and yeasts have been used successfully as biosorbent due to low cost, high efficiency, larger surface area, regeneration of biosorbent stability against acidic media and selectivity for some analytes (Ucun, 200; Javanbakht 2014).

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In this study, RrDB was used for separation and enrichment of Cd(II) from various water samples. R. ruber is a species of the genus Rhodococcus, which is a part of the phylogenetic group nocardioform actinomycetes (Gibson, 2003). Since they are equipped with a large number of enzymatic activities, unique cell wall structure, and suitable biotechnological properties. Rhodococcus strains may be utilized as industrial organisms, primarily for biotransformations and biodegradation of many organic compounds (Bell, 1998). Rhodococci can thus be applied in environmental remediation and in the pharmaceutical and chemical industries (Van der Geize, 2004; Otari, 2014).

The objective of the present work is to evaluate the usability of RrDB as a new SPE system based on biosorption for the separation and preconcentration of cadmium ions from in commerical drinking water, tap water, river water and wastewater samples followed by FAAS determinations. Various experimental and analytical parameters, such as pH of sample solution, sample volume, flow rate of sample solution and eluent, volume and concentration of eluent, amount of adsorbent, effect of other ions, and capacity of adsorbent were investigated. The proposed method was applied for the determination of trace amounts of Cd(II) in various water samples and the method was verified using standard reference materials. MATERIALS & METHODS Apparatus The analysis was performed by ContrAA 300, a HR-CS FAAS (Analytik Jena AG, Jena, Germany), equipped with a 50 mm burner head. An acetylene flame (C2H2) was used for atomization of Cd(II). All absorption lines of elements in the spectral range of 185–900 nm can be analytically evaluated by using a Xe short-arc lamp as a continuum lamp source. The spectral background of the sample in the HR-CS FAAS is always corrected directly on the analysis line simultaneously and independently. The operating conditions for Cd(II) by HR-CS FAAS are given in Table 1. Table 1. The operating conditions for HR-CS AAS for cadmium determination. Parameters Wavelength, nm

Cd(II) 228.8018

Flow rate of C2H2-air, L h-1

50

Burner height, mm

6

Evaluation Pixels, pm

3

Background correction

Simultaneous

Growth of Rhodococcus ruber Single colony isolates of Rhodococcus ruber JCM 0205 (JCM, Japanese Collection of Microorganisms) were grown up on GYEA streak plates at 30°C for 72 hours. These cultures were then used to inoculate sterile mineral salts medium (500 ml) in 2 L

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Reagents All solutions were prepared using ultrapure water (specific resistance 18 MΩ cm) from a Milli-Q purification system (Millipore Corporation, Massachusetts, USA). Standard solutions of analyte were prepared from their 1000 mg L−1 stock solutions (Merck). In this study, buffer solutions (Merck) of sodium acetate-acetic acid (for pH 3–5), sodium monohydrogen phosphate–potassium dihydrogen phosphate (for pH 6–8), and ammonium chloride–ammonia (for pH 9) were used. Calibration standards of Cd(II) was obtained from suitable dilutions of the stock solutions.

3

flasks, which were subsequently incubated at 30°C with shaking at 160 rpm in an orbital shaker. R. ruber cells were harvested at logarithmic phases by centrifugation at 9000 rpm for 20 minutes. The cells were stored by freezing them at -70°C, followed by freeze drying (Kariptaş, 1999). Preparation of separation column Adsorption column was prepared according to the literatüre (Ciftci, 2014). The glass column was 10 cm in length and 0.8 cm internal diameter. A small amount of glass wool was placed on the top and the bottom of the RrDB (0.3 g) to avoid disturbance during the sample passage. The biomass bed height in the column was approximately 2.0 cm. It was washed successively with water, 2 mol L−1 HCl and HNO3 solutions, respectively. Before each cycle, the column was preconditioned by passing the blank solutions in working pH. Separation/adsorption procedure The proposed method was tested by using standard test solutions before its application to the various water samples. The standard test solutions were prepared as follows: 1 mL of 5 mg L−1 of Cd(II) standard solution was added to 2 mL buffer solutions in a volumetric flask. The pH was adjusted by adding 0.1 mol L−1 HCl or 0.1 mol L−1 NaOH to the medium. Afterwards, final volume of sample was diluted to 50 mL with distilled water. The column was preconditioned by passing the aqueous solutions of working pH through column and then the model solution was passed through the column at a flow rate of 5 mL min−1. The adsorbed Cd(II) on the column was eluted with 5 mL of 2 mol L−1 HCl solution that has a flow rate of 3 mL min−1. Cadmium was analysed for the determination of metal concentrations by HR-CS FAAS. Analysis of water sample Tap water was taken from Kırşehir water supply network while the river water was collected from Kızılırmak River. Commercial natural drinking water was bought directly in a local supermarket in Kırşehir, Turkey. Wastewater sample was collected from the Organized Industrial Site in Kırşehir. Analyses of samples were performed in compliance with the recommended preconcentration procedure. In order to confirm the validity of the developed procedure, this method was applied for the determination of in a Standard Reference Material; SRM 1640a, trace elements in natural water.

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RESULTS & DISCUSSION

4

Effect of sample solution pH pH is an important factor for adsorption processes for the purposes of separation and preconcentration. In order to find the optimum pH, the model solution was adjusted to the desired pH with the buffer solution. These solutions were then

passed through the column at 5 mL min−1. Optimum recoveries were achieved when pH was between 6.5 and 8.0 for Cd. Therefore, pH 7.0 was selected as an optimum pH for adsorption and recovery of the analyte ions for subsequent studies. Effect of type, concentration, and volume of eluent The elution of Cd(II) ions on RrDB were studied by using HCl solution at varying concentrations (0.1–2.0 mol L−1) as a stripping agent. The results demonstrated that 5.0 ml of solution of 2 mol L-1 HCl can be used for maximal recovery of Cd(II) ions. Effect of sample flow rate and sample volume The retention of metal ions on the sorbent depends on the flow rate of the metal ions solution. (Ezoddin, 2010). The influence of metal ions sorption on RrDB was investigated by varying the flow rate of the sample solution in the range of 2–8 mL min−1, and passing the solution through the microcolumn using a peristaltic pump. The optimum value for the flow rate of the sample solution was found up to 5 mL min−1. Above this value, the recovery decreased gradually. Therfore, the flow of 5 mL min−1 for Cd(II) was selected. To obtain a high preconcentration factor, a larger volume of sample solution is required (Mortada, 2015). For that reason, the volumes of sample solution containing 5 μg each of Cd2+ was varied from 50–1000 mL. The metal was preconcentrated on the RrDB by applying the proposed procedure. Quantitative recovery (>95%) of Cd(II) was obtained up to 750 mL. Maximum preconcentration factors for Cd(II) was found to be as 150. Effect of interfering ions The efficiency of the proposed method in the extraction and preconcentration of Cd(II) ions in the presence of various cations and anions was examined by applying the recommended column procedure on solutions containing 5 μg L−1 of Cd(II) with addition of various concentrations of potential interfering ions. The results indicated that high concentrations of some cations and anions have no significant effects on the separation and determination of cadmium ions at pH 7.0. Analytical features By applying the optimum experimental conditions, the characteristics of the method are presented in Table 2.

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Precision and Application of the Procedure To investigate the accuracy of the proposed method, a recovery work was initially conducted. Known amounts of the analyte ions were added to commerical drinking water, tap water, river water, and wastewater samples; afterwards, the proposed method was applied.

5

Table 2. Analytical performance and optimum condition of the proposed method for determination of cadmium. Cd(II) pH

7.0

Amount of biomass (mg)

300

Eluent volume (2 mol L−1HCl) (mL)

5

Eluent flow rate (mL min )

3

Sample flow rate (mL min )

5

−1

−1

Maximum sample volume (mL)

750

Enrichment factor

150

Detection limit (μg L−1)

0.86

Precision (R.S.D, N=7) (%)

1.8

Analysis of real samples In order to assess the applicability and feasibility of method for the analysis of real samples with different matrices, the proposed procedure was applied to the separation and recovery of ions from commerical drinking water, tap water, river water, and wastewater samples. The results are given in Table 3. Table 3. Levels of for Cd ions in various water samples Cd(II) Sample

Added (µg L-1)

Found* (µg L-1)

Commerical drinking water

0

ND

5.0

4.9.0.4±

Tap water

0

ND

5.0

5.1 ±0.4

0

3.1±0.3

10.0

12.8±0.5

0

12.7±0.6

5.0

17.5±0.5

River Wastewater

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N.D: Not detected *Mean and standard deviation from three determinations.

6

Recovery %

98.0

102 97.7 98.8

CONCLUSION The present investigation shows that the Rhodococcus ruber dry biomass an effective and inexpensive biosorbent for the uptake of cadmium from various water samples. ACKNOWLEDGEMENTS This work was supported by the Ahi Evran University Scientific Research Projects Coordination Unit. Project Number TIP.E2.16.012.

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with vortex-mixing for determination of palladium and silver in water samples by flame atomic absorption spectrometry, Water Science Technology, 69, 580-586. Morales J, Sa´nchez L., Bijani S., Martı´nez L., Gaba´s M., Ramos-Barradob J. R. (2005), Electrodeposition of Cu2O: an excellent method for obtaining films of controlled morphology and good performance in Li-ion batteries, Electrochemical and Solid-State Letters 8, 159-162. Mortada W.I., Kenawy I.M.M., Abdelghany A.M., Ismail A.M., Donia A.F., Nabieh K.A. (2015), Determination of Cu2+, Zn2+ and Pb2+ in biological and food samples by FAAS after preconcentration with hydroxyapatite nanorods originated from eggshell, Materials Science and Engineering C, 52, 288–296. Otari S.V., Patil R.M., Nadaf N.H., Ghosh S.J., Pawar S.H. (2014), Green synthesis of silver nanoparticles by microorganism using organic pollutant: its antimicrobial and catalytic application, Environmental Science and Pollution Research, 21, 1503–1513. Pytlakowska K., Kozik V., Dabioch M. (2013), Complex-forming organic ligands in cloudpoint extraction of metal ions: a review, Talanta, 110, 202–228. Saçmacı Ş., Ş Kartal., Y Yılmaz., M Saçmacı., C Soykan. (2012), A new chelating resin: synthesis, characterization and application for speciation of chromium(III)/(VI) species, Chemical Engineering Journal, 181, 746–753. Saçmacı Ş. Yılmaz Y., Kartal S., Kaya M., Duman F. (2014), Resting Eggs as New Biosorbent for Preconcentration of Trace Elements in Various Samples Prior to Their Determination by FAAS, Biological Trace Element Research, 159, 254–262. Silva E.L., Roldan P.S. and Giné M.F. (2009), Simultaneous preconcentration of copper, zinc, cadmium, and nickel in water samples by cloud point extraction using 4-(2-pyridylazo)resorcinol and their determination by inductively coupled plasma optic emission spectrometry. Journal of Hazardous Materials 171, 1133–1138. Someda H.H. and Sheha R.R. (2006), Solid Phase Extractive Preconcentration of Some Actinide Elements Using Impregnated Carbon, Journal of Nuclear and Radiochemical Sciences, 7, 37-43. Soylak M., Unsal Y.E., Kizil N., Aydin A. (2010), Utilization of membrane filtration for preconcentration and determination of Cu(II) and Pb(II) in food, water and geological samples by atomic absorption spectrometry, Food and Chemical Toxicology, 48, 517– 521. Ucun H., Bayhan Y.K., Kaya Y., Cakici A., Algur O.F. (2002), Biosorption of chromium (VI) from aqueous solution by cone biomass of Pinus sylvestris, Bioresource Technology, 85, 155–158. Van der Geize R. and Dijkhuizen L. (2004), Harnessing the catabolic diversity of rhodococci for environmental and biotechnological applications. Current Opinion Microbiology, 7, 255-61. Yildiz D., Kula I., Şahin N. (2013), Preconcentration and Determination of Cd, Zn and Ni by Flame Atomic Absorption Spectrophotometry by Using Microorganism Streptomyces Albus Immobilized on Sepiolite, Eurasian Journal of Analytical Chemistry, 8, 112-122.


IBCESS

TEMPORAL VARIATIONS OF EASTERN BLACK SEA AEROSOL İlker Balcılar1, Abdullah Zararsız2, Yakup Kalaycı2, Güray Doğan3 and Gürdal Tuncel1 Department of Environmental Engineering, Middle East Technical University, Ankara, Turkey. [email protected] 2 Turkish Atomic Energy Authority, Ankara Nuclear Research and Training Center. 3 Department of Environmental Engineering, Akdeniz University, Antalya, Turkey. 1

ABSTRACT

Keywords: Eastern Black Sea; Trace elements; Aerosol; Temporal variations; EDXRF.

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Concentration of 17 trace elements and SO42- were determined in coarse (PM2.5-10) and fine (PM2.5) fraction aerosol samples that is collected at a high altitude site (Torul, 40°32’34”N 39°16’57”E) on the Eastern Black Sea coast of Turkey between March 2011 and November 2012. Collected samples were analyzed by energy dispersive x-ray fluorescence (EDXRF) using an Oxford ED–2000 Spectrometer. Measured concentrations varied between approximately 0.44 ng m-3 for As and 2216 ng-3 for SO42-. Soil-derived elements, Al, Si, K, Ca, Ti, V and Fe, had higher concentrations in the coarse fraction as expected. Results indicated that the concentrations of elements showed well-defined seasonal variations. Crustal elements had higher concentration in summer. Na, an element generally associated with sea salt, had also higher concentrations in summer season, suggesting a strong crustal contribution to Na concentration at our station. Anthropogenic elements As, Zn, Pb and Cr had comparable concentrations in both season. Cu, Ni, and V, had higher concentrations in winter season due to the sources close to sampling point. Crustal enrichment factors of Ni, Cu, Cr, As, Pb, Zn and SO42- varied between 12 for Ni and 800 for SO42-. Upper atmospheric flow climatology showed that most frequent flow direction was the sector between W and N.

9

INTRODUCTION Aerosols in the atmosphere originate from both from natural (wind-blown, sea spray, frost fires) and anthropogenic (fuel and biomass burning, industrial processes, traffic emissions) sources (Güllü et al., 2005; Tokgöz, 2013). Global aerosols production estimates suggest that since they interact with solar radiation (IPCC, 2001) and effect micro-meteorological processes (Bhaskar and Mehta, 2010), aerosols may affect Earth’s energy balance and hence the climate (Öztürk et al, 2012; Tecer et al, 2012). Therefore, accurate data on the quantity and characteristics of pollutants at the source and receptor sites are required in order to assess perturbations in the biogeochemical cycles of trace elements (Rasmussen, 1998). Aerosol composition is highly variable in space and time because of the diverse sources (Rostogi and Sarin, 2009). Temporal variations of concentrations depends on several factors including; the existing and anthropogenic sources, transport pattern, and meteorological factors (e.g. wind speed, wind direction, precipitation). Since most of these patterns change in time, chemical compositions of aerosols show short and long term variations (Solomon et., 1996). Studies conducted in the Black Sea region of Turkey are few (Hacısalihoğlu et al., 1992; Karakaş et al., 2004; Doğan et al., 2010; Tecer et al., 2012) and even some are conducted in urban sites. In this study size-distributed PM samples (PM2.5-10 and PM2.5) were collected at a high altitude rural station located northeast part of Black Sea region of Turkey. This paper presents a temporal variation data set on the size distributed chemical composition of existing aerosol at the northeast part of Black Sea region. MATERIALS & METHODS

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The sampling station (40°32’34”N 39°16’57”E) is located at a Ministry of Forestry, log storage area located at approximately 5 km to southwest of the Torul village at the eastern Black Sea coast of Turkey. The altitude of the station is 1115 m above sea level. The station is approximately 70 km from the coastline and shown in Figure 1. Sampling was performed between March 2011 and December 2012. The sample collection period was 24 h for all collected samples and sampling were interrupted only to change filters. In total, 270 daily coarse and fine aerosol were collected.

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Figure 1. Location of the sampling station Daily coarse (PM2.5-10) and fine (PM2.5) aerosol samples were collected on polycarbonate (Nuclepore) filters using Gent Stacked Filter Unit (SFU) (Hopke et al., 1997) The device has a PM10 pre-impactor and contains two filters, a coarse and a fine filter, placed in series. The air enters the unit through the preimpactor designed to have a 50% collection efficiency at 10 μm equivalent aerodynamic diameter (EAD) and particles with diameters larger than 10 μm are removed in this stage. Air is then drawn through two polycarbonate sequential filters. The SFU was operated at a fixed flow rate of 16.7 l min-1. The initial and second filter were 47 mm in diameter with pore sizes of 8 and 0.4 μm, respectively. Coarse and fine fractions of the aerosol were collected separately on these filters. The flow through filters will result in the collection of the particles with diameters larger than 2.2 μm on the initial filter (coarse fraction). Those with diameters smaller than 2.2 μm pass through the initial filter and were held on the backup filter (fine fraction).

Collected samples analyzed by XRF using an Oxford ED–2000 energy dispersive X-Ray Spectrometer for trace elements including Na, Mg, Al, Si, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Ba and Pb at Sarayköy research center of the Turkish Atomic Energy Agency (TAEK). An Ag anode X-ray tube with maximum current of 1000 μA

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Before sampling, the coarse and fine filters were placed into a constant humidity chamber at room temperature, in open plastic Petri dishes, for at least 24 h, in the clean area to reach a constant humidity. Afterwards, they were weighed with a microbalance. After sampling, the filters were transferred to the laboratory. They were placed in the constant humidity chamber, again for 24 h, and then weighted under exactly the same conditions as the empty filters to determine coarse and fine particle mass.

11

and with maximum voltage of 50 kV was used as a source of excitation. The EDXRF was calibrated with spiked synthetic standards and accuracy of results were tested by running NIST SRM 2783 (Air Particulate Matter on Filter Media) along with samples. RESULTS & DISCUSSION Coarse (PM2.5-10) and fine (PM2.5) fraction concentrations of elements key statistics for each of these variables measured between 2011 and 2012, at Torul station is summarized in Table 1. Concentrations in the data set varied between 0.44 ng m-3 for As and 2216 ng m-3 for SO42-. Concentration of Na which is a good marker element for sea salt, on the other hand, is fairly low, compared to Na concentrations reported for Turkish coastal stations, due to 70 km distance between the station and coastline. Its concentration is higher in the coarse fraction as expected. Concentrations of soil-derived elements, including Al, Si, K, Ca, Ti, V and Fe are higher in the coarse fraction as soil particles have mass median diameter of approximately 3.0 to 3.5 μm (Kuloğlu and Tuncel, 2005). Coarse-to-fine ratios of these elements varied between 1.2 for K and 3.1 for Ca. Concentrations of elements with mixed natural and anthropogenic sources, such as, Ti, V, Cr, Mn and Ni have comparable concentrations in coarse and fine fraction particles, which is understandable because part of their concentrations are due to presence of coarse soil particles.

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Pollution-derived elements and ions measured in this work, including SO42-, Cu, Zn, As and Pb have higher concentration in fine fraction. Their coarse-to-fine median ratios varied between 0.2 for SO42- ion and unity for As. Sulfate ion has smallest coarse-to-fine ratio, which is followed by Pb (C/F ratio is 0.5). Coarse to fine ratios of elements is a reflection of their size distribution in the atmosphere. Lead and SO42were reported to have smallest mass median diameter (0.7 μm for Pb and 0.5 μm for SO42-) in an impactor study performed at the Eastern Mediterranean (Kuloglu and Tuncel, 2005).

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Summer and winter concentrations of elements are given in Table 2. Summer, in this study, is the period between May and October and winter is the remainder of the year. This division is based on the rainfall amount. Summer and winter seasons include month in which 20% and 80% of the annual rainfall occurs, respectively. The division of seasons was based on rainfall, because it is the one of the most important parameters affecting seasonal variation in concentration of elements (Güllü et al., 1998; 2005).

Table 1. Statistical summary of measured concentrations of elements (ng m-3) Coarse (PM2.5-10) Mean

STD

Fine (PM2.5)

Median

Min

Max

Mean STD Median

Min

Max

Na

67 ± 96

42

1.0

794

31 ± 39

25

1.17

473

Mg

140 ± 350

70

8.8

3295

69 ± 144

39

0.87

1771

Al

380 ± 870

210

14

8706

178 ± 355

111

0.51

4457

Si

1100 ± 3100

518

36

33038

445 ± 854

300

2.97

11522

SO4

310 ± 230

210

1.4

3384

1760 ± 1620

1260

10.49 26263

K

140 ± 380

94

13

5503

90 ± 147

69

0.92

2137

Ca

8003 ± 1700

480

35

20760

270 ± 526

153

0.52

5601

Ti

200 ± 2400

13

0.33

36252

21 ± 59

8.1

0.04

466

V

39 ± 190

1.0

0.04

1083

3.9 ± 4.5

1.0

0.12

12

Cr

11 ± 40

6.0

0.01

537

7.1 ± 8.9

4.7

0.03

98

Mn

21 ± 71

10

0.49

909

11 ± 16

8.1

0.21

171

Fe

730 ± 3200

240

4.3

36223

500 ± 1100

159

2.99

6430

Ni

1.9 ± 3.6

0.9

0.02

19

3.7 ± 16

2.0

0.04

185

Cu

9.2 ± 19

3.3

0.03

112

6.9 ± 14

2.6

0.12

78

Zn

31 ± 43

21

0.01

326

28 ± 29

19

0.01

169

As

0.2 ± 0.7

0.2

0.001

8.9

0.2 ± 0.4

0.2

0.00

4.79

Ba

3.5 ± 2.0

3.3

0.22

9.3

3.9 ± 2.7

3.2

0.85

11

Pb

3.8 ± 5.8

1.3

0.07

45

4.1 ± 5.2

2.4

0.15

43

Sodium is frequently used as marker element to quantify sea salt contribution to aerosol mass. Since more active storm activity over the sea generates higher quantities of sea salt in winter season, concentrations of sea-salt elements are expected to be higher in winter. However, summer-to-winter median concentration ratio for Na, in this study, is 1.64, which is comparable to corresponding ratios observed in crustal elements. Higher Na concentrations during summer season is probably due to approximately 70 km distance between the coastline and our station. Since sea salt

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Summer-to-winter median concentration ratios of elements varied between 1.96 for Al and 0.08 for V. Elements with the highest summer-to-winter ratio are crustal elements and SO42-. Higher concentrations of crustal elements during summer, is due to easier resuspension of soil particles during dry summer season. Since soil is damp or ice covered in winter resuspension of local soil is less likely. This scenario results in higher concentrations of soil-related elements in summer. Concentration of SO42-is also higher in summer as it is secondary specie produced by photochemical oxidation of SO2. More vigorous photochemical activity is expected in summer owing to higher solar flux.

13

particles are coarse they are quickly scavenged from atmosphere within few kms from coastline and crustal contribution start to dominate Na concentrations at distances far from the coastline. A crude calculation using Mason’s (1966) crustal compilation, Al and Na concentrations in our samples demonstrated that, on the average, more than 90% of observed Na concentration at Torul station can be accounted for by crustal aerosol, which explains higher concentrations of Na recorded in summer season. Table 2. Summer and winter season concentrations of elements at Torul station. (Concentrations are in ng m-3) Summer AVG ± STD

Ti

106 ± 120 (86¶) 208 ± 417 (128) 545 ± 986 (402) 1312 ± 2472 (936) 2549 ± 6893 (1965) 246 ± 601 (176) 1094 ± 2193 (708) 28 ± 42 (19)

V

Na Mg Al Si SO4 K

AVG ± STD STD

Median

N

S/W ratio

136

110 ± 159 (52)

48

126

318 ± 701 (101)

42

137 166 164 158

696 ± 1637 (205) 2334 ± 6210 (610) 1420 ± 1000 (1130)

57

210 ± 316 (135)

71

157

2 ± 0 (2)

1

Cr

15 ± 18 (13)

Mn

146

52

69

65

1.64 1.27 1.96 1.53 1.73 1.31 1.09

60

1.18

151 ± 357 (21)

8

0.08

114

26 ± 74 (15)

53

0.89

120

1.43

44

42 ± 128 (17) 3253 ± 7354 (910) 9.9 ± 10.0 (5.4)

59

Ni

29 ± 47 (24) 478 ± 469 (411) 3.3 ± 1.4 (3.5)

15

0.65

Cu

7.7 ± 6.3 (5.5)

13

34 ± 49 (11)

23

0.51

Zn

52 ± 38 (43) 0.48 ± 1.3 (0.35) 8.1 ± 3.4 (8.2)

23

83 ± 100 (44) 0.34 ± 0.24 (0.30) 6.1 ± 0.9 (6.0)

28

0.99

Fe

As FP3

N

1381 ± 2626 (649) 685 ± 4696 (16)

Ca

14

Median

Winter

Ba Pb

32

112 12

37

36 4.0

7.1 ± 4.4 (6.1) 28 15 ± 23 (6.5) 10 ¶ Numbers in parenthesis are median concentrations of elements

1.33

1.17 1.36 0.94

Elements with mixed origin, like K, Ti and anthropogenic elements, such as As, Zn, Pb and Cr have comparable concentration is summer and winter seasons. This pattern is not unique and reported in many studies around the Black Sea and Eastern Mediterranean basins. The only exceptions to this general pattern is observed in concentrations of Cu, Ni, and V, which have higher concentrations in winter season. This unexpected pattern can be an artifact for V because it is measured in only one sample in our summer period, but the pattern is real for Cu and Ni. Earlier studies performed in the Eastern Mediterranean and Black Sea basins demonstrated that elements that have higher concentrations in winter have sources close to the sampling point (Karakas et al., 2004; Doğan et al., 2008; Koçak et al., 2007), which is attributed less efficient wet scavenging of local particles from atmosphere. Higher winter season concentrations of Ni and Cu may be to their relatively local sources. Smelters at Samsun, Murgul (Artvin), Georgia and Ukraine (Dzubay et al., 1984) can be nearby sources that can affect seasonal variation in concentrations Ni and Cu.

Crustal Enrichment factor (EFc) of an element can be calculated using the following relation: (1) Where (Cx/CAl)Sample is the ratio of the concentration of the test element (Cx) to that of Al in the sample. /(Cx/CAl)Soil is the same ratio in soil. Aluminum is a generally used as crustal reference element, because its main source in aerosol is the crustal material (except for very small areas around Al plants) and it can be measured reliably using variety of analytical techniques. Other crustal markers, such as Fe, Sc, rare earths etc. can also be used as crustal reference element. However, they are not as widely used either because they may have non-crustal sources (like Fe) or their measurements in atmospheric aerosol is not as easy as measurement of Al (like Sc, rare earth element). Global compilations of soil composition are used to calculate “(Cx/CAl)Soil” in the relation. The EF values calculated in this work are based on the data given for the mean abundance’s of elements in the Earth’s crust by Mason (1966). Since composition of local soil around the sampling point may be different from that of Mason’s (1966) compilation, Elements with EFc values < 10 are not considered as enriched. The EFc value of 1.0 (or 10 indicates enrichment and non-crustal source for the test element.

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Crustal enrichment factors of elements The chemical composition of the aerosols in the atmosphere is controlled by mixing of various natural and anthropogenic components and the extent to which the mixing occurs will vary both in space and time. Enrichment factors (EF) provide qualitative information on the crustal and non-crustal components in aerosol population (Zoller et al., 1974). Enrichment factors are generally calculated relative to soil composition as soil is the most common component in aerosol population, EF can also be calculated relative to any source for which a reliable reference element is available.

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Winter

Summer

1000

EFc

100

10

1

0,1

Fe

Al

Na

Ti

Mg

K

V

Ba

Ca

Mn

Ni

Cu

Cr

As

Pb

Zn

S

Figure 2. Seasonal crustal enrichment factors Enrichment factor of elements in, summer and winter seasons are given in Figure 2. Elements Fe, Na, Ti, Mg, K, V, Ba, Ca and Mn have enrichment factors means average over the test case, oi and pi are the observed and forecasted O3 concentration values on day i, N is the number of days in the test set, pi’= pi – om and oi’= oi – om , with om the average observed O3 concentration. The index of agreement is a dimensionless index bounded between 0 (showing no agreement at all) and 1 (perfect agreement of the time series). These indices make assessments of the global performance of the model; in order to check the forecast accuracy. The subject details were explained elsewhere (Yıldırım, 2010).

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N

1 N 2 ∑ (oi − pi ) N i =1

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RESULTS & DISCUSSION In this study, the SPSS 15 software and Excel were used for processing data, developing equation and presenting figures. One of the criteria considered for the model input variables is the cross-correlation coefficient. The cross-correlation results were given in Table 1. As seen from Table 1, there are correlation between ozone and independent parameters and among all parameters each other. As a particle, PM10 and PM2.5 have the highest correlation with the other parameters. Except wind speed, relative humidity and air pressure, all other parameters have negative correlation with ozone. However, wind speed has the lowest correlation with ozone and the other parameters. Due to existence of correlation, all parameter were employed as independent parameters for ozone modelling. Table 1. Cross-correlation of the parameters used in the modelling. PM10 PM2.5 PM10 PM2.5 NO NO2 NOx CO TEM WD WS RH AP O3

NO NO2 NOX

1,00 0,88 0,72 0,70 0,88 1,00 0,71 0,73 0,72 0,71 1,00 0,85 0,70 0,73 0,85 1,00 0,74 0,75 0,96 0,97 0,81 0,92 0,70 0,71 0,36 0,32 0,34 0,33 0,42 0,36 0,37 0,38 0,13 0,08 0,16 0,12 -0,48 -0,31 -0,40 -0,32 -0,44 -0,31 -0,33 -0,25 -0,41 -0,55 -0,48 -0,45

CO

TEM WD

WS

RH

AP

O3

0,74 0,81 0,36 0,42 0,13 0,75 0,92 0,32 0,36 0,08 0,96 0,70 0,34 0,37 0,16 0,97 0,71 0,33 0,38 0,12 1,00 0,73 0,35 0,39 0,15 0,73 1,00 0,29 0,34 0,09 0,35 0,29 1,00 0,85 0,14 0,39 0,34 0,85 1,00 0,10 0,15 0,09 0,14 0,10 1,00 -0,37 -0,35 -0,33 -0,33 -0,33 -0,30 -0,34 -0,28 -0,28 -0,29 -0,48 -0,53 -0,15 -0,15 0,05

-0,48 -0,31 -0,40 -0,32 -0,37 -0,35 -0,33 -0,33 -0,33 1,00 0,89 0,17

-0,44 -0,31 -0,33 -0,25 -0,30 -0,34 -0,28 -0,28 -0,29 0,89 1,00 0,21

-0,41 -0,55 -0,48 -0,45 -0,48 -0,53 -0,15 -0,15 0,05 0,17 0,21 1,00

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In this study, there equation were developed for ozone prediction using two different model employing air quality and meteorological parameters as described above. The models and their equations were given in Table 2. As seen from Table 2, the best representative equation was developed by Model 2 showing better R (0,755) performance for production of the equation.

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The performance of the models developed had been checked using RMSE, IA and Correlation coefficient which were given in Table 3. Model 2 has better prediction performance than Model 1 for the both season. However, Model 2 has the highest performance for prediction of winter data showing RMSE=5.15, IA=0.80 and R2=0.66. If the seasons compared, the winter season data was forecasted better than summer season data by the both models. Due to ozone’s natural structure, there are more complex condition in summer period rather than winter period. It is thought that this is the main reason for better prediction

of winter season values. The results of the prediction by Model 2 were presented in Figure 1 and Figure 2. As seen from these figures, the model prediction values follow the measured values and even it follows the lowest and highest values for winter season data in Figure 2. Table 2. The model equations used in ozone prediction. R

Equations for ozone prediction O3= –2288,213 + 0,425*(PM10) – 0,910*(PM2.5) -0,156*NO + 0,11*(NO2) – 0,001*(CO) – 1,592*(TEM) + 0,069*(WD) + Model 1 0,576 5,752*(WS) – 0,201*(RH) + 2,275*(AP) ln(O3)= –196,195 + 0,5*ln(PM10) – 0,851*ln(PM2.5) – 0,969*ln(NO) - 0,597*ln(NO2) + 1,382*ln(NOX) + 0,261*ln(CO) + 0,183*ln(TEM) Model 2 0,758 + 0,043*ln(WD) + 0,168*ln(WS) – 0,177*ln(RH) + 28,513*ln(AP) NO: Nitrogen monoxide, NO2: Nitrogen dioxide, NOX: Nitrogen oxides, CO: Carbon monoxide, TEM: Temperature, WD: Wind direction, WS: Wind speed, RH: Relative humidity, AP: Air pressure

Table 3. Performances of the models used in the prediction.

RMSE IA R2

Winter season data for prediction (between 20/12/2015 and 05/03/2016)

Model 1

Model 2

Model 1

Model 2

15,17

15,20

17,20

5,15

0,47

0,50

0,37

0,38

0,46

0,80

0,56

0,66

Figure 1. The prediction results against the observed values for winter season data using Model 2.

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Summer season data for prediction (between 24/06/2016 and 18/08/2016)

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Figure 2. The prediction results against the observed values for summer season data using Model 2.

CONCLUSION In this study two model were used to develop statistical equation to forecast short time air quality in Giresun city. Following results have been obtained and conclusions have been drawn: • In cross-correlation, except wind speed, relative humidity and air pressure, all other parameters have negative correlation with ozone. • The best representative equation was developed by Model 2, power law model showing better R (0,755) performance than Model 1. • Model 2 has the highest performance for prediction of winter data showing RMSE=5.15, IA=0.80 and R2=0.66. • Prediction values of Model 2 follow the measured values and even it follows the lowest and highest values for winter season data. • Even the Model 2 forecast better values, the prediction values are needed to perform better values.

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• The data used for equation development is not enough, so more air quality data are needed to develop better equation that predict more precise value.

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• Ozone and atmospheric hydrocarbons (HCs) are closely affect each other. So, to obtain better ozone prediction value, HCs concentrations in the measuring site must be detected and involved into regression.

REFERENCES 1. Annand, W. J. D. and Hudson, A. M. (1981), Meteorological effects on smoke and sulfur dioxide concentrations in the Manchester Area. Atmospheric Environment 15 (5), 799-806. 2. Chaloulakou, A., Saisana, M., Spyrellis, N., (2003), Comparative assessment of neural networks and regression models for forecasting summertime ozone in Athens. Sci. Total Environ. 313, 1-13. 3. Cobourn, W., (2007), Accuracy and reliability of an automated air quality forecast system for ozone in seven Kentucky metropolitan areas. Atmos. Environ. 41, 58635875. 4. Giresun, (2015), Giresun City Environment Report, Directorate of Environment and Urbanism, Giresun. 5. Jorquera H., Perez R., Cipriano A., Espejo A., Victoria Letelier M., and Acuna G.(1998), Forecasting ozone daily maximum levels at Santiago, Chile, Atmospheric Environment, Volume 32, N.20, pp. 3415-3424. 6. Khare, M and Sharma, P., (2002), Modelling Urban Vehicle Emissions, pp11-32. WIT press, Southampton, London. 7. Kocijan, J., Gradisar, D., Boznar, M.Z., Grasic, B. and Mlakar, P., (2016), On-line algorithm for ground-level ozone prediction with a mobile station, Atmospheric Environment 131, 326-333. 8. Lissens, G., Mensik, C., Dumont, G., (2000), SMOGSTOP: a new way of forecasting ozone concentrations at ground level. Int. J. Environ. Pollut. 14 (1e6), 418-424. 9. Logan, J.A., (1999), An analysis of ozonesonde data for the troposphere: recommendations for testing 3-D models and development of a gridded climatology for tropospheric ozone. Journal of Geophysical Research 104, 16115–16149. 10. Monks, P.S., (2000), A review of the observations and origins of the spring ozone maximum. Atmospheric Environment 34, 3545–3561. 11. Moustris, K.P., Nastos, P.T. Larissi, I.K. and Paliatsos, A.G. (2012), Application of multiple linear regression models and artificial neural networks on the surface ozone forecast in the greater Athens area, Greece, Advanced in Meteorology, 2012, pp. 1–8. 12. Shi, J., P. ve Harrison R., M. (1997), Regression modelling of hourly NOx and NO2 concentratıon in urban air in London, Atmospheric Environment Vol. 31, No. 24, s4081-4094.

14. Yıldırım, Y., Sokhi, R.S. and Luhana, L. (2003a), Modelling of NO2 Concentration Near a Major Road in the UK Using a Regression Approach. In: Proceedings of the 4th Intern. Conference in Urban Air Quality. Measurements, Modelling and Management (UAQ2003), 25-27 March 2003, Prague (CZ), Ranjeet S. Sokhi, J. Brechler (Eds.) (2003) 1-4, ISBN 07509547.

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13. Vingarzan, R.,(2004), A review of surface ozone background levels and trends, Atmospheric Environment 38, 3431–3442

15. Yıldırım, Y., Bayramoğlu, M., Hasiloğlu, S. (2003b), Prediction of sulfur dioxide

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daily levels in the city of Zonguldak using an adaptive neuro-fuzzy based method, Fresenius Environmental Bulletin, V. 12, No. 10, pp. 1173-1179. 16. Yıldırım Y., (2010), Prediction of Hourly Roadside NO2 Concentration Using a Fuzzy Logic Approach (ANFIS), Fresenius Environmental Bulletin, 19(7), 1320-1327.

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17. Zhang, Y., Bocquet, M., Mallet, V., Seigneur, C., Baklanov, A., (2012), Real-time air quality forecasting, part I: history, techniques, and current status. Atmospheric Environment Vol. 60, 632-655.

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IBCESS

EVALUATION OF LAND LOSS FOR ENVIROMENTAL FACTS: THE ATASU DAM EXAMPLE Osman Tuğrul BAKİ, Egemen ARAS and Banu YILMAZ Karadeniz Technical University, Of Technology Faculty, Civil Engineering Department, Trabzon, Turkey [email protected]

ABSTRACT Atasu Dam stays 17 km southwestern of Trabzon Maçka district and built in Galyan Valley. The dam built between dates 1998-2010 for the purpose of generating energy and drinking water. The dam got into the use in 2011. By the 50 years drinking water demand of Trabzon will supply by this dam. The dam has got 35 billion cubic meter water – holding capacity so that approximately 971,5 decare terrain stayed hidden under the water. The purpose of this study, evaluation of land loss both calculating costs and environmental affects after the construction of Atasu Dam which areas stay upstream. The costs have been taken at General Directorate of State Hydraulic Works, the Atasu Dam Reservoir Revise Expropriation Report. In addition, the ecological balance analyzed after the construction dam reservoir.

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Keywords: Atasu Dam, ecological balance, land loss, Trabzon.

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INTRODUCTION Atasu Dam is located at Atasu District, on the Galyan River in Trabzon City in Turkey. The dam construction began in 1998. The location is near the one of the tributary Galyan streams which stays 16.5 km southern of Trabzon-Erzurum highway. The dam is next to Milan Street and stays 3 km distant from upstream of the Galyan stream and Değirmendere meets. Atasu dam has been built to produce energy and domestic water between the years 1998 to 2010. It currently stands 118 m high from the foundation. Atasu dam is a concrete-faced rock fill dam. The dam is designed to provide 91 hm3 annual water demand of Trabzon and producing electricity. The embankment volume is 3.8 hm3, lake area at normal water level is 0.83 km2 and expected storage capacity of 35.75 hm3. Thalweg level 205.00 m, maximum water level 320.60 m. The power plant, which provides the electric from the dam, has 45 MW installed capacity and aims to produce 150 GWh electric for a year. (General Directorate of State Hydraulic Works) The drinking, using and industrial water demand of Trabzon and its towns are being supplied with Atasu Dam. Atasu Dam was built for providing drinking, using and industrial water and producing energy to Ortahisar, Yomra and Akçaabat districts for following 50 years. (Aras, 2011)

Figure 1. The location of Atasu Dam (Alemdağ S., 2006)

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The reservoir began filling in December 2010. At 2011, the water level risen the expected capacity. The risen water level eventually inundates several countries near the dam, causing significant change in land use, topography and evaporation that are expected to alter regional weather and climate patterns. 32

Figure 2. Atasu Dam Reservoir and Galyan Valley Environmental Effects of Dam Plant There are two types of alteration with dam construction. One of this alteration is related to living space. It causes changes residential areas and missing cultural areas. Secondary is about physical conditions. These are destruction of flora and fauna or necessity of migration, less agriculture terrain and every type of environmental pollution. These following changing can be classified as social and environmental effects; Social effects, • Loosing agriculture terrain, trees and fruit orchard, • Loosing homes and other farm-buildings • Lose of access common property, especially fields, • Involuntary relocation, • Loosing means of existence • Removing people whose means of existence are agriculture and livestock • Cutting of relations with society FP6

• Reducing social supports.

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Environmental effects can be classified as; • Increasing biological diversity missing, • Loosing fishery, • Changing water supply, • Destruction of cultural, historical and mineral resources, • Missing archeologic, scenic and touristic areas, • Physical and chemical environmental effects, • Environmental effects of flora and fauna, • Effects on substructure. METHOD At this paper, numeric and linguistic data are taken at relevant institutions, fieldworks, a literature review and satellite pictures are taken at Google Earth. In this study the effects of land loss in the dam reservoir area evaluated after the dam construction. STUDY SITE AND STUDIES Due to dam construction on a river there will be substantial spatial differences. Especially the area, where the dam will be constructed and the dam reservoir area had to be clear off and the existing residence must be removed. The dam construction has been effected Temelli Village, Yeniköy, Alaçam Village and Oğulağaç Village Maraboğlu District. Because of this effect resident person have to be expatriated to city center and neighbor village. After this migration people changed their hometown and they lose their communication with each other. As a result of this people’s social organization disbanded and their ethos differentiation comes true. Reel assets of the dam expropriation area can be sorted like this;

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1- Agricultural lands a- Agricultural lands in reservoir area b- Agricultural lands at construction area 2- Domestic and other buildings (road, bridge) 3- PTT telephone lines 4- Energy lines 5- Mill

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Agriculture and livestock constitute the basis of economy in the reservoir area. The settlement is known as a village, which involves several districts. There are dispersed

settlement. The buildings in the settlement are reinforced, wooden, stone setting and masonry. Barns stay downstairs in buildings. 89 buildings have been flooded at dam reservoir area. Table 1. Number of Expropriated Assets Type Of Enacted Reel Assets

Quantities

Home (Reinforced)

61

Home (Stone Setting)

15

Home (Wooden)

12

Home (Masonry)

1

Total

89

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Figure 3. Google Earth View of the Atasu Dam Reservoir Area at 30/07/2002

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Figure 6. Google Earth View of the Atasu Dam Reservoir Area at 14/11/2015 There are stabilized road between reservoir area and villages. Roads covered with asphalt where Trabzon-Erzurum highway connects with Galyan River. There are stabilized road reach up to Galyan River Valley. Some part of roads at Temelli Village, Konaklar Village and Cangar Village had inundated. These areas had subject to reposition. Approximately 500 graves transported to other graveyards by dweller. Libadomos Mosque, which is in the Oğulağaç Village in Maraboğlu District, stayed under water.

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5.320 km village roads inundated at reservoir area. There are 3 concrete bridges on roads and these are covered with water. There aren’t any buildings related with tourism.

37

Figure 7. A View of Dam Reservoir Area

The population quantity of reservoir area observed between 2000 – 2014 years and it seems that the dweller quantity decrease gradually.

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Figure 8. A View of Dam Reservoir Area

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Table 2. By the Year Population Changing Table at the Atasu Dam Reservoir Area (Turkish Statistical Institute) Year 1985 1990 2000 2007 2008 2009 2010 2011 2012 2013 2014 2015

Atasu Town Oğulağaç Village Temelli Village Alaçam Village Yeniköy Village Population Population Population Population Population 772 841 164 275 2262 771 841 130 265 4436 347 463 104 158 2370 275 472 64 87 2199 310 431 115 101 1996 305 413 99 99 1770 303 405 87 89 1626 317 389 82 83 1427 318 380 86 76 1345 321 401 92 90 1264 328 373 83 97 1207 317 377 82 89

The expropriation area at the reservoir area cover irrigation field, bottom land, sloping land, shrubland, unproductive coppice, and non-agricultural land.

Type of Land

Foot Print (da)

Range (%)

Irrigation Field

4

0.5

Bottom Land

59

6.0

Sloping Land

562.5

58.0

Unproductive Coppice

13

1.5

Shrubland

283

29.0

Non-Agricultural Land.

48

5.0

971.5

100

Total

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Table 3. Land Distribution at Dam Reservoir Area

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Figure 9. Land Distribution at Dam Reservoir Area Loosing agricultural estates, trees and fruit gardens causes less production of vegetable, fruit, and forestry activity. Our country hasn’t got substantial forest cover. Dam construction threatens available forest potential by destruction forests. Besides forest the underwood plants are affected. Forest destruction gives rise to financial damage. Although the region shown forest on the map, the region isn’t forested area in real. The region unproductive coppice, where barely firewood and rangeland, where aren’t any economic activity. Hazelnut, corn, and bean are the most important economic activity at the Atasu Dam reservoir area. Valuable and fertile agricultural lands stayed under the water. Annual plant cultivation is making at some place of reservoir area. The people, who live there, cope with livestock. Synthetic and animal manures are using at agriculture. There isn’t any industrial plant at reservoir area. Although there isn’t any industrial plant, there are 2 mills which grinds corn and wheat. The whole commercial activity in the dam reservoir area is based on agricultural marketing. There isn’t any commercial activity else.

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627.7 da agricultural area, 250 non-agricultural areas, and total 877.7 da area had expropriated.

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Table 4. Expropriation Values of Land at the Atasu Dam Reservoir Area at 1992 Type Of Enacted Reel Assets

Quantities (da)

Unit Price (TL/da)

Extended Price(TL)

YT1

119,3

15.225.000,00

1.816.342.500,00

YT2

353,4

12.500.000,00

4.417.500.000,00

YT3

80,7

10.500.000,00

847.350.000,00

YT4

11,3

6.700.000,00

75.710.000,00

TT1

59

18.000.000,00

1.062.000.000,00

ST2

4

3.968,00

15.872,00

Shrubland

250

279.000,00

69.750.000,00

Total

8.288.668.372,00

Where YT1, YT2, YT3, YT4 represents sloping and non-agricultural lands, TT1 represents bottom lands and ST1 represents irrigation fields. (General Directorate of State Hydraulic Works) Table 5. Expropriation Values of Residence at the Atasu Dam Reservoir Area at 1992 Type Of Enacted Reel Assets

Quantities

Unit Price (TL/da)

Home (Reinforced)

61

79.259.328,00

4.834.819.008,00

Home (Stone Setting)

15

20.303.552,00

304.553.280,00

Home (Wooden)

12

7.965.867,00

95.590.404,00

Home (Masonry)

1

30.762.959,00

30.762.959,00

Total

5.265.725.651,00

Extended Price (TL)

In consequence of the researches settlement status, means of living, trade and industrial status, forestry activities analyzed at construction zone at Atasu Dam. Together with the water retention at dam 971.5 da land, 89 houses, 3 concrete bridges, 2 mills, 1 mosque, village roads, PTT phone lines, energy lines have inundated. The dweller had taken 5.265.725.651, 00 TL money from house expropriation and 8.288.668.372,00 TL money from land expropriation. And the total they took 13.554.394.023,00 TL from expropriation. As a result of expropriation the dweller emigrated to Trabzon city center and neighborhood villages. With this migration they abandoned their livelihoods, milieu and hometowns. After this migration the population of region decreased. The dam, which provide a solution to the water and electric demand

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CONCLUSION

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of Trabzon city, carried problems. Though dweller took money from expropriation, they are not happy because they left hometown. The main aim would be analyzing negative effects of the project and decreasing these effects. REFERENCES 1.

Alemdağ S., and Gürocak Z., (2006). The Bearing Capacity of the Basalts at the Atasu (Trabzon) Dam Site, Science and Eng. J of Fırat University, 18 (3), 385-395. (In Turkish) 2. Aras E., and Berkün M. (2011), the New Epoch at Trabzon Drinking Water: Atasu Dam, 6. Urban Infrastructure Symposium, Antalya, Turkey. (In Turkish) 3. Bakırcı M., (2016), the Effects of Dams on the Spatial Reorganization: The Case of Melen Dam, Marmara Geographical Journal, 33, 439-464. (In Turkish) 4. Gleick P. H. (2009), Three Gorges Dam Project, Yangtze River, China, Water Briefs, 139150. 5. Matete M., Rashid H. (2004), An Ecological Economics Framework For Assessing Environmental Flows: The Case of Inter-Basin Water Transfers in Lesotho, Global And Planetary Change, 47, 193-200. 6. Sönmez M. E. (2012), the Negative Impacts of Dams on Environment and Their Samples in Turkey, Gaziantep University Journal of Social Science, 11, 213-231. (In Turkish) 7. The Atasu Dam Reservoir Revise Expropriation Report (1992), General Directorate of State Hydraulic Works, XII. Regional Directorate, Trabzon. (In Turkish) 8. Toker E. (2010), Investigating Land Use Change and Land Degradation in Çoruh Watershed Due To Borçka and Deriner Dams, Department of Forest Engineering, Artvin Çoruh University. (In Turkish) 9. Tosun H., Seyrek E., Türköz M., and Savaş H. (2007), Seismic Hazard and Total Risk Analyses Of Concrete-Faced Rockfill Dams in Turkey, 4th International Conference on Earthquake Geotechnical Engineering, Thessaloniki, Greece. 10. Xibao X., Yan T., and Guishan Y. (2013), Environmental Impact Assessments of the Three Gorges Project In China: Issues and Interventions, Earth – Science Reviews, 124, 115-125. 1111 Üslü A. (2011), Environmental Effect Cost Analysis of Ilısu Dam, Master Thesis, The Graduate School of Natural and Applied Sciences Civil Engineering Program, Karadeniz Technical University (In Turkish).

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URL‘s http://www.uludagsozluk.com/r/atasu-baraj%C4%B1-ve-hidroelektrik-santrali-477312/ (Fig 7) (date of access 09.05.2016) http://www.panoramio.com/photo/58717746 (Fig.8) (date of access 09.05.2016) http://www.emo.org.tr/ekler/e2677218bdbec95_ek.pdf (date of access 23.03.2016) http://tr.wikipedia.org/wiki/Atasu,_Ma%C3%A7ka (date of access 09.03.2016) http://arsiv.zaman.com.tr/2003/11/02/karadeniz/h8.htm (date of access 11.03.2016) http://www.uludagsozluk.com/r/atasu-baraj%C4%B1-ve-hidroelektrik-santrali-477312/ (date of access 11.03.2016) https://plus.google.com/photos/107772360222178684719/ album/5872993305917451249/5872993751811068002?authkey=CLiyibzI2NjgpQE (date of access 11.03.2016) http://www.tripmondo.com/turkey/trabzon/bahcekaya/picture-gallery-of-bahcekaya/ (date of access 11.03.2016) http://www.kuzeymedya.com/gundem/burasi-halfeti-degil-galyan.htm (date of access 09.03.2016) http://www.yerelnet.org.tr/belediyeler/belediye.php?belediyeid=126996 (date of access 03.03.2016)


IBCESS

3D SPATIAL DISTRIBUTION OF WATER QUALITY PARAMETERS IN KARACAÖREN-II DAM RESERVOIR Firdes Yenilmez Department of Environmental Engineering, Akdeniz University, Antalya, Turkey [email protected] ABSTRACT

Keywords: 3D spatial distribution, water quality, Karacaören-II Dam Reservoir, Matlab.

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Karacaören-II Dam Reservoir is located in Burdur, Turkey. The major tributary is the Aksu River. The surface area and volume of the reservoir at normal water surface elevation is 2 km2 and 48 hm3, respectively. The reservoir is considered as a drinking water supply for Antalya in the near future. So, water quality in the reservoir and in the influent river is so important. However, the water quality in Aksu River and Karacaören-II Dam Reservoir is under stress due to wastewater discharges, surface runoff from agricultural sites, solid wastes and fish farming. The water quality of the reservoir has been mentioned as Category A3 (Drinkable water following physical, chemical and advanced treatment and disinfection) in recent studies. Therefore, problematic zones in terms of water quality should be determined and necessary precautions should be taken to improve the water quality in the reservoir. In this study, 3D distributions of dissolved oxygen (DO), specific conductivity (SC), pH and temperature in the Karacaören-II Dam Reservoir was constituted using the data obtained from the in-situ measurements along the water depth at 22 sampling locations. A script written in Matlab was used to obtain the 3D spatial distributions to evaluate problematic zones in terms of water quality. While a relatively homogenous distribution is obtained for SC along the water depth, DO exhibits an anoxic zone at the bottom of the reservoir. The lower DO concentrations along the water depth are observed in the inlet of the reservoir. There is no big difference in temperature values (min:12.15 oC and max:14.54 oC) along the depth since measurements conducted in November. This study may be beneficial to determine water sampling points along the depth and to identify segments in water quality modelling studies.

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INTRODUCTION Karacaören-II Dam Reservoir with an average depth of 20.5 m is a relatively deep reservoir which is located in Burdur, Turkey. In large deep water bodies like Karacaören-II Dam Reservoir, a thermocline layer can be formed due to change of temperature with depth. This layer acts as a physical barrier to exchanges between surface and bottom layers and causes the depletion of DO in deeper parts (Chehata et al., 2007; Yenilmez, 2014). Segmentation, physical configuration of water body, is an important step especially in the water quality modelling studies. Different types of segments like the epilimnion (surface water), hypolimnion (subsurface), upper benthic and lower benthic layers can exist in the water body. The segment type plays a significant role in bed sedimentation and in certain transformation processes. The arrangement of underlying segments is important when light has to pass from one segment to the next in the water column, or when material is buried or eroded in the bed. Segment sizes are determined more by the spatial and temporal scale of the problem being analyzed than by the characteristics of the water body or the pollutant. The important spatial characteristics within a segment must be homogenous. This constraint sometimes can be relaxed by sensible averaging over width, depth and length. The segment sizes are also affected by the usual spatial variability of the water quality concentrations (Wool et al., 2001; Yenilmez 2007; Yenilmez and Aksoy, 2013). In this study, 3D spatial distributions of dissolved oxygen (DO), specific conductivity (SC), pH and temperature in the Karacaören-II Dam Reservoir were evaluated using 3D graphs constituted by a script written in Matlab. This study may be beneficial to determine water sampling points along the depth. Moreover, the study will be useful in the segmentation of the reservoir based on spatial variability of the examined water quality parameters for the future water quality modelling studies.

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MATERIALS & METHODS

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Karacaören-II Dam Reservoir with an area of 2.34 km2 is a recreational and culture fishing area located in Burdur, Turkey (Figure 1). The reservoir was constructed on Aksu River between 1988 and 1993 for irrigation and supply energy. Furthermore, it is being considered as a possible potable water supply for Antalya in near future. Therefore, protection and management of the water quality in the reservoir is so important. The water quality of Karacaören-II Dam Reservoir has been mentioned as drinkable water following physical, chemical and advanced treatment and disinfection (Category A3) in recent studies. So, the evaluation of the 3D spatial distribution of water quality parameters will be helpful for better management of the water quality in the reservoir. For this purpose, in-situ measurements along the depth were made for DO, SC, pH and temperature at 21 sampling locations using a YSI 6600 EDS multiparameter water quality sonde. Locations of sampling points are displayed in Figure 1. After the collection of water quality data, a script was written in Matlab to obtain the 3D spatial distributions of the water quality parameters.

Figure 1. Location of Karacaören-II Dam Reservoir RESULTS & DISCUSSION

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The data which were obtained from 21 sampling locations in Karacaören-II Dam Reservoir was statistically analyzed. According to results given in Table 1, no big difference was observed in temperature and pH values along the depth. However, the variance in dissolved oxygen along the depth was considerably higher than the others. DO is a good indicator of water quality in water bodies and one of the primary concerns of limnologists and water resource engineers (Karamouz et al., 2009). Minimum dissolved oxygen is 0.34 mg/L and it reveals the presence of an anoxic zone in the sampling point 8 (K8 in Figure 1).

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Table 1. Statistics for DO, SC, pH and temperature at 21 sampling locations Parameter

Minimum

Maximum

Mean

Stdev

Temperature ( C)

12.15

14.54

13.38

0.27

pH

7.45

7.76

7.58

0.06

SC (µS/cm)

373

444

384

8.86

DO (mg/L)

0.34

8.31

4.30

1.33

o

When 3D temperature data was examined (Figure 2), it was realized that temperature values are higher in the entrance of Aksu River to the reservoir with respect to the rest of the reservoir. Furthermore, there is no big difference in temperature values (min:12.15 oC and max:14.54 oC) along the depth since measurements conducted in November. While a relatively homogenous distribution was obtained for SC along the water depth (Figure 3), DO concentrations are considerably lower at the bottom of the reservoir (Figure 4). Moreover, DO exhibits anoxic zone in some parts of the reservoir. The lower DO concentrations along the water depth are observed in the inlet of the reservoir. Especially the zones within black circles in Figure 4 are problematic zones in terms of DO. These zones are not suitable for water abstraction. When Figure 2 - Figure 5 are evaluated, 10 m depth interval for vertical segments is seen as enough for the autumn. It can be different from other seasons. Temperature(oC)

0

14.5

-5

14

-10

-15

Z

13.5 -20

-25

13

-30

12.5

-35

-40 4.1305

4.131

4.1315

4.132

4.1325

4.133 Y

4.1335

4.134

4.1345

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Figure 2. X-Z View of 3D temperature data

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4.135

4.1355 6

x 10

Specific Conductivity(mS/cm)

0

440 -5 430 -10 420

Z

-15

410

-20

-25

400

-30

390

-35

-40 4.1305

380

4.131

4.1315

4.132

4.1325

4.133 Y

4.1335

4.134

4.1345

4.135

4.1355 6

x 10

Figure 3. X-Z View of 3D SC data

Dissolved Oxygen(mg/L)

0

8 -5 7 -10 6 -15

-20 4 -25 3 -30 2 -35 1 -40 4.1305

4.131

4.1315

4.132

4.1325

4.133 Y

4.1335

4.134

4.1345

4.135

4.1355 6

x 10

Figure 4. X-Z View of 3D DO data

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Z

5

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pH

0

7.75

-5 7.7 -10

7.65

Z

-15

-20

7.6

-25 7.55 -30 7.5 -35

-40 4.1305

4.131

4.1315

4.132

4.1325

4.133 Y

4.1335

4.134

4.1345

4.135

4.1355

7.45

6

x 10

Figure 5. X-Z View of 3D pH data CONCLUSION Results obtained in this study indicate that evaluation of 3D spatial distribution of water quality parameters is useful for the determination of water quality model segments. The depth interval for vertical segments in this study determined as 10 m in Karacaören-2 Dam Reservoir. Relatively homogenous distribution was observed for SC along the water depth. There are problematic zones for DO in some parts of the reservoir. Special attention should be given to these areas for better management of the reservoir. This study should be repeated other seasons as well to determine the seasonal variations in the zones. Acknowledgement: This study is financially supported by the Akdeniz University Research Fund (Project no. FBA-2015-462).

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REFERENCES

48

1.

Chehata, M., Jasinski, D., Monteith, M. C., & Samuels, W. B. (2007), Mapping ThreeDimensional Water-Quality Data in the Chesapeake Bay Using Geostatistics. Journal of the American Water Resources Association, 43(3), 813–828. doi:10.1111/j.17521688.2007.00065.x.

2.

Karamouz, M., Kerachian, R., Akhbari, M., & Hafez, B. (2009), Design of River Water Quality Monitoring Networks: A Case Study, Environmental Modeling & Assessment,14(6), 705714. doi:10.1007/s10666-008-9172-4.

3.

Wool, T. A., Ambrose, R. B., Martin, J. L., Comer, E. A. (2001), Water Quality Analysis Simulation Program (WASP) Version6.0 User’s Manual, U.S. Environmental Protection Agency, Atlanta, GA.

4.

Yenilmez, F. (2007), Modeling The Water Quality In Uluabat Lake. M.S. Thesis, Middle East Technical University, The Department of Environmental Engineering.

Yenilmez, F. (2014), Spatial Data Analysis for Monitoring and Prediction of Selected Water Quality Parameters in Reservoirs: Porsuk Dam Reservoir Case, PhD Thesis, Middle East Technical University, Department of Environmental Engineering.

6.

Yenilmez, F., Aksoy, A (2013), Comparison of Phosphorus Reduction Alternatives in Control of Nutrient Concentrations in Lake Uluabat (Bursa, Turkey): Partial Versus Full Sediment Dredging. Limnologica-Ecology and Management of Inland Waters, 43 (1), 1-9.

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5.

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IBCESS

COMPARISON OF SEX AND SIZE STRUCTURE OF CAPOETA TRUTTA POPULATIONS IN ATATURK AND KARAKAYA DAM LAKES Ayse Gul SAHIN1, Unal ISPIR2 and Rıdvan TEPE1 Elazig Directorate of Fisheries Research Station, Elazig, Turkey Inonu University, Fisheries Faculty Battalgazi, Malatya, Turkey [email protected]

1 2

ABSTRACT The aim of this study is to analyze the sex and size structure of Capoeta trutta populations in Ataturk and Karakaya Dam Lakes. The survey was conducted in April and May 2015. Were got 32 (16 males and 16 female) and 16 (10 males and 6 female) sexually mature C. trutta from Ataturk and Karakaya Dam Lake, respectively. The sex percentage was determined as 50 % males and females in Ataturk Dam Lake. But, the number of males and females of C. trutta population in the Karakaya Dam Lake is the females (37.50%) over the males (62.50%). Fork length of fish ranged from 25.00 cm to 46.10 cm and body weight of fish ranged from 154 g to 786 g. The linear measurements of the males in the C. trutta population is significantly smaller, than those of the females in Ataturk and Karakaya Dam Lakes.

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Key Words: Ataturk dam lake, Capoeta trutta, growth parameters, Karakaya dam lake

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INTRODUCTION The family Cyprinidae is the largest of all fish families. The cyprinid genus Capoeta is represented from South China, North India, Middle East and Anatolia (Fazeli et al., 2016). C. trutta has a fusiform body, very little scales, sub-terminal mouth and the noticeable characteristic of this fish is black points on body (Niya et al., 2015). C. trutta is one of the most common and widely distributed fish species in Turkey (Kalkan, 2008).This kind is an economically important fish and the object of significant commercial fishery in Ataturk and Karakaya Dam Lakes. The relationship between sex and size structure of fish are important and useful parameters in fish biology, stock status, fisheries evaluation of fish populations (Bagenal and Tesch, 1978; Bolger and Connolly, 1989; Georgiev et al., 2015). Many studies were also conducted on the biological characteristics and growth of the economically important cyprinid, including C. trutta, which inhabits the Ataturk and Karakaya Dam Lakes of Turkey (Kalkan, 2008; Oymak et al., 2008; Oymak et al., 2011; Duman and Gul, 2013). This study aims to determine sex and size structure of the C. truttain Ataturk and Karakaya Dam Lakes. MATERIALS & METHODS In this study, 32 individuals (16 males and 16 female) and 16 individuals (10 males and 6 female) sexually mature C. trutta from Ataturk and Karakaya Dam Lake, respectively. The survey was conducted in April and May 2015. Fish collection sites are shown in Figure I.

Arguvan

Battalgazi

Doğanyol

A

B

Sampled fishes were transferred to the laboratory. The sex of the fishes was defined to include the total body length, the standard body length, the trunk length, the head length, the body height, the body width and the circumference were measured. The live weight of the fishes (W, g) was weighed, using an electronic scale, with accuracy

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Figure 1. Map of the Ataturk (A) and Karakaya (B) dam lake

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up to 0,1g. The linear measurements (mm) were carried out, using a measuring board, a triangle and a tape. The Statistical processing of the data was made, using software Minitab Statistic Program. RESULTS A specific feature of the sex structure of C. trutta population is the equal number of females and males in the population of the Ataturk Dam Lake. But, in the population of Karakaya Dam Lake show that the bigger number of males (62.50%), than females (37. 50%).The average body measurements of C. trutta, inhabiting Ataturk Dam Lake is given in Table 1. The total body length of the fish is 29.30±3.25 cm and the respective values vary between 25-38.1 cm. The longest body height is 6.66±0.83 cm, with a variation between 5.2 and 8.9cm. The largest body width is 3.74±0.65 cm, where the minimum is 2.8 cm and the maximum is 5.4 cm. The average live weight of the C. trutta is 320.00±126.79 g, where the minimum is 174 g and the maximum is 720 g.The linear measurements of the males in the C. trutta population from Ataturk Dam Lake are smaller than those of the females (Table 1). Male ‘s total body length is 4.60% smaller than the one of the female sand no statistically significant differences with females (P>0.05). The same is valid for the trunk length, the body height and circumference. Males’ live weight is 24.60% lower than the females (P74

6.3-8.1 25-183 29-375 100-700 47-466 1.7-34.3 0.11-22.8

Total Coliform (CFU/100 ml)

10-2.4x107

200.5-7x105

> 2.4x108

56-8x107

Fecal Coliform (CFU/100 ml)

0-3.4x105

50-1.4x103

-

0.1-1.5x108

Parameters

Reuse of greywater Reuse of grey water has lots of benefits such as protection of high quality fresh water reserves with reducing the need to tap water, reducing the load of treatment plants and septic reactors, reducing of energy and chemical usage, reuse of residual nutrients during irrigation and better plant growth. According to the studies which based on 120 liters of water consumption per person/day, a 4-5 people family which use a grey water recycling system achieve saving up to 80,000 liters of tap water per year.

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Table 2. Greywater characteristics due to source of grey water (Li et al, 2009)

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Greywater needs to be collected separately to reduce of the load of sewage treatment processes. As a result of this, the treatment systems become more efficient and can be operated at lower cost. Greywater treatment may be applied to housing estates, dormitories, business centers, hotels, shopping malls, social foundations-complex where with high population. Treated greywater can be used in toilet tanks, washing machines, irrigation of greenfields, rough cleaning as car washing, firefighting, ponds, industrial processes as cooling towers. Besides being hygienic and aesthetic, the treatment process should contribute to environment and economy for reuse of grey water (Dixon et al., 1999). The legal standards for re-use of greywater keep users away from health risks. These standards may vary according to intended use based on greywater treatment processes which are also vary. Some type of greywater requires advanced treatment techniques while some can be treated using basic classical methods.

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Table III shows the different reuse applications of grey and wastewater from different countries. These studies analyzed certain parameters including pH, turbidity (NTU), BOD5, total coliform and fecal coliform as removal quality parameters. Occasionally total suspended solids, residual chlorine, total nitrogen and total phosphorus were also analyzed.

74

6-9

5-9,5

-

ABD (Environmental Protection Agency)

UK (Environmental Agency)

World Health Organization

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5.88.6

Japan

6-9

-

Germany

China

pH

Country

75

-

1.0, indicating net volatilization for these PAHs, while fluorene, phenanthrene and anthracene showed volatilization tendency at some sampling sites, deposition tendency for others. Fugacity ratios for high molecular weight PAHs were