Volume II

PROCEEDINGS OF THE ENVIRONMENT & GREEN CHEMISTRY SYMPOSIUM 2007 12th ASIAN CHEMICAL CONGRESS

Volume II Edited by Lee Yook Heng Wong Ling Shing

Published by Institut Kimia Malaysia (Malaysian Institute of Chemistry) 127B, Jalan Aminuddin Baki, Taman Tun Dr Ismail, 60000 Kuala Lumpur Website: http://www.ikm.org.my 15 August 2007

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CONTENTS OF VOLUME II ECOLOGICAL SOLID WASTE MANAGEMENT EVALUATION INSTRUMENT: A STANDARD GUIDE TO DETERMINE SWM EFFECTIVENESS AT BARANGAY 9-A, DAVAO CITY, PHILIPPINES

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Albert B. Jubilo, Lilia F. Panchito and Angelita G. Fernandez COMPARISON OF DIFFERENT TYPES OF COATINGS IN HEADSPACE SOLID PHASE MICROEXTRACTION FOR THE ANALYSIS OF PESTICIDE RESIDUES IN VEGETABLES AND FRUITS

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Chai Mee Kin and Tan Guan Huat DETERMINATION OF SOME HEAVY METALS IN BANGMOD CANAL BANGKOK

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G.Mathap, B. Limchawfar, S. Sujaritvanichpong, S. Santikoon, S. Chongcharoen and R. Thanawadee A SURVEY ON ELECTRONIC WASTES AND THEIR DISPOSAL IN DAVAO CITY

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Jenith L. Banluta, Johna Marie R. Tabanguil, Evtri E. Tabanguil, Albert Jubilo DEGRADATION AND LEACHING OF ACEPHATE CHLORPYRIFOS IN TROPICAL SOILS OF SARAWAK

AND

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Lian-Kuet Chai, Norhayati Mohd-Tahir & Hans Christian Bruun Hansen COMPARATIVE IMPLTMENTATION OF ra 9003 OF THE TWO BARANGAYS IN DANAO CITY, PHILIPPINES

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Maribel R. Blones DDT RESIDUE IN SOIL AND WATER IN AND AROUND ABANDONED DDT MANUFACTURING FACTORY

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M. Rasul Jan, Jasmin Shah, Kashif Gul and Mahmood A. Khawaja COMBINATION OF ADVANCED OXIDATION PROCESS (AOP) WITH MEMBRANE BIOREACTOR (MBR) SYSTEM FOR ZERO SLUDGE PRODUCTION Putri. N. Faizura, M. Roil Bilad, Hilmi Mukhtar

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NEMATODE PARASITES OF FISH AS AN INDICATOR OF POLLUTION OF SEA

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Rafia Azmat, Shahina Fayyaz and Nasira Kazi STUDY ON UTILIZATION OF ACTIVATED SLUDGE PROCESS FOR HEAVY METALS-CONTAINING WASTEWATER

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Soon-An Ong, Eiichi Toorisaka, Makoto Hirata and Tadashi Hano A MODEL FOR THERMAL CONDUCTIVITY OF ARTIFICIAL METHANE HYDRATE SEDIMENT SAMPLE

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Tomoya Tsuji, Toshihiko Hiaki, Michica Ohtake, Taro Kawamura, Takeshi Komai, Seong-Pil Kang APPLICATION OF THE EXCESS CARBON DIOXIDE PARTIAL PRESSURE (EpCO2) FOR ASSESSMENT OF THE TROPHIC STATE OF SURFACE WATER IN SOME VIETNAMESE RIVERS

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Trinh Anh Duc, Choi Sung-Uk, Nguyen Huong Giang, Vu Duc Loi, Le Lan Anh INFLUENCE OF SURFACTANT TYPES ON THE CORRELATION OF RETENTION FACTOR AND HYDROPHOBICITY OF TRIAZOLE FUNGICIDES USING MICELLAR ELECTROKINETIC CHROMATOGRAPHY

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Wan Aini Wan Ibrahim, Dadan Hermawan, Mohamed Noor Hasan and Mohd Marsin Sanagi DETOXICIFICATION ABILITY OF JAPANESE FUNGI HIRATAKE AND BUNASHIMEJI FOR EXPLOSIVE CONTAMINATED LAND

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Do Ngoc Khue, Phan Son Duong, Pham Kien Cuong, Trinh Xuan Gian, Do Binh Minh, To Van Thiep, Morinaga T. APPLYING LOW ULTRASONIC IN GRIGNARD REACTIONS FOR SYNTHESIS OF THE INSECTS’ PHEROMONES AND ATTRACTANTS

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Dang Chi Hien, Nguyen Cong Hao, Nguyen Cuu Thi Huong Giang, Le Thanh Son, Nguyen Thanh Danh SUITABILITY OF OIL PALM FIBER AND KERNEL AS MEDIA IN DETERMINING OF OXYGEN DEMAND IN SUB-SURFACE FLOW OF CONSTRUCTED WETLAND Ahmad Md. Noor, A.Y. Siew, H.L.H. Chong, H.P.S. Abdul Khalil, S. Suryani

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ECOLOGICAL SOLID WASTE MANAGEMENT EVALUATION INSTRUMENT: A STANDARD GUIDE TO DETERMINE SWM EFFECTIVENESS AT BARANGAY 9-A, DAVAO CITY, PHILIPPINES Albert B. Jubilo1, Lilia F. Panchito2 and Angelita G. Fernandez3 1

Engineering and Architecture Division, Ateneo De Davao University, Jacinto Street, Davao City 8000; Philippines; Cell No. +639193639644; [email protected] 2 College of Engineering, University of Mindanao, Matina Campus, Davao City 8000, Philippines; Cell No. +639186347446; [email protected] 3 College of Engineering, University of Mindanao, Matina Campus, Davao City 8000, Philippines; Cell No. +639189248104

ABSTRACT: Solid Waste Management (SWM) refers to the collection, transportation, final disposal and recycling of solid wastes. The study aims to determine the usefulness and effectiveness of the SWM evaluation instrument in the implementation of SWM programs. The study ascertained that the SWM instrument is useful and effective in the implementation of the SWM program at the barangay level. The instrument set out the goal, criteria, brief description of their eco-waste management system. It revealed that Barangay 9-A adhered to the criteria, passed necessary ordinances and policies, implemented programs, regularly monitored the implementation and encouraged social participation. Key words: Solid waste management, sanitary practices, waste segregation INTRODUCTION Solid waste is an environmental problem that has reached critical proportions in the Philippines. Due to a growing population, rapidly increasing consumption and increasing urbanization, waste generated in the Philippines is estimated at 19,700 tons per day. SWM is the responsibility of local government units (LGUs), i.e., barangays (the smallest political unit composed of 50-100 families), municipalities, cities and provincial governments. There are 41,392 barangays, 1502 municipalities, 116 cities and 71 provinces nationwide. There was a nationwide search for barangay models for eco-waste management systems last 2003-2004. The criteria were (1) understanding of RA 9003 (Ecological Solid Waste Management Act), (2) ordinances passed, (3) designation of point persons, (4) composting and recycling, (5) social participation, and (6) earnings from avoidable disposal costs. Last January 2004, the Department of Interior and Local Government (DILG), Department of Environment and Natural Resources (DENR), National Ecological Solid Waste Management Commission, Earth Day Network Phils., Clean and Green Foundation, Zero Waste Recycling Movement of the Philippines, Linis-Ganda, EcoWaste Coalition and other non-governmental organizations came up with Nationwide Search for Model Barangays for Eco Waste Management System 2003-04 as mandated by RA 9003 (known as Ecological Solid Waste Management Act). The 5

goals were to help Barangays comply with RA 9003, to assist communities and monitor the progress of barangays’ segregation scheme initiatives, and installation of ecology centers for composting and material recovery facilities (MRF’s) for recycling, to recognize, reward, support, help ensure sustainability of the Barangay ESWM program, and to establish a rating or grading system for all Barangay Eco Waste Programs to mark improvement or decline of said programs. It also provided cash prizes, trophies and certificate of compliance of RA 9003 to all qualifiers. Furthermore, the search evaluation system provided the following criteria: 1. Barangay Council members must have read and understood RA 9003 and its enabling Implementing Rules and Regulations; 2. Has passed local ordinances regarding the segregation of waste at household levels, segregated collection and segregated destinations for compostables, recyclables and residuals; 3. Has designated officials or point persons to carry out and supervise compliance with said ordinance; 4. Identified a physical center for composting and recycling; 5. Visible evidence of social participation; 6. Savings from Hakot-Tambak method. Earnings from avoidable disposal costs. The components of the self-evaluation form include: 1. Education 1.1 Training of government personnel, private citizens and other groups 1.1 Mobilization of Citizenry 1.2 Media Campaign 2. Engineering 2.1 Segregation and Collection Facilities 2.2 Materials Recovery Facility for Biodegradable Waste 2.3 Materials Recovery Facility for Non-Biodegradable Waste 3. Enforcement 3.1 Ten Year Plan; Incentives and Penalties 3.2 Waste Reduction Program and Rehabilitation of Waterways, Drainage, etc. 4. Economics and Sustainability 4.1 Livelihood Created and Financial Returns 5. Special Consideration 5.1 Miscellaneous Matters Hence, the proponents of this study came up with a study to determine the effectiveness of that established evaluation instrument in terms of solid waste management. Research Problem. The purpose of the study is to ascertain the usefulness of the SWM evaluation instrument in the implementation of SWM programs. Specifically, it sought to accomplish the following objectives: 1. To verify whether the barangay adhere to the criteria or not; 2. To find out policies and mechanisms in the SWM implementation; 3. To ascertain the sustainability of the SWM programs; 4. To validate the SWM self-evaluation of the barangay; and 5. To determine the efficacy of the SWM evaluation instrument. 6

Significance of the Study. Findings derived from this study will be valuable to the following in many ways: (1) Residents. They will be informed of the effectiveness of the SWM program of the Barangay and maybe encouraged to participate in all environmental-related activities; (2) Barangay Officials. The findings could provide information to local government unit in the promulgation of policies and guidelines on the enhancement of SWM program. Research Design. The study used the descriptive method of research. Interview with the Barangay officials was carried out to find out the programs undertaken and their effectiveness. Interview with some residents was made to know the problems of implementation and concerns. Field observation was made to appraise the community. The study was limited only to the results of the interview and field observation. Secondary data were used to support the study. Respondents. The respondents of the study were the Barangay officials, which include the Barangay chairman, one “kagawad” (councilman), secretary, treasurer, and some residents. Research Instruments. This study used interview and field observation to gather data. Statistical Treatment. Qualitative analysis of data was used. RESULTS AND DISCUSSION Adherence to the Criteria. Based on the six criteria set out in the evaluation instrument, Baranagy 9-A complied substantially all. It is manifested that the Barangay Council members read and understood RA 9003 and its enabling Implementing Rules and Regulations since they all attended related seminarworkshops and trainings; passed local ordinances regarding the segregation of waste at household levels, segregated collection and segregated destinations for compostables, recyclables and residuals, which include Barangay Ordinance No. 03, series of 2003, Ordinance No. 03-A, series of 2003, Ordinance No. 12, Series of 2004, and Ordinance No. 13, series of 2004; has designated officials or point persons to carry out and supervise compliance with said ordinance; identified a physical center for composting and recycling; there was a visible evidence of social participation; and there were earnings from avoidable disposal costs. Policies and Mechanisms in the SWM Implementation. Barangay 9-A passed the following ordinances in the SWM implementation: 1. Barangay Ordinance No. 03, series of 2003 – An Ordinance Creating The Barangay Ecological Solid Waste Management Committee (BESWMC) 2. Barangay Ordinance No.03 – A, series of 2003 – Barangay Ecological Solid Waste Management Ordinance 3. Barangay Ordinance No. 12, series of 2004 – An Ordinance to Establish Garbage Disposal Collection Points and Setting of Dumping Time in the Barangay 4. Barangay Ordinance No. 13, series of 2004 – An Ordinance to Establish Material Recovery Facility (MRF) 5. Barangay Ordinance No. 14, series of 2004 – An Ordinance Adopting Solid Waste Management Plan 7

The Barangay conducted several information drive, seminars and trainings in coordination with City Environment and Natural Resources (CENRO), such as: 1. Brgy. Ecological Solid Waste Management Symposium – March 1, 2003, with 65 participants. 2. Orientation on Brgy. Ecological Solid Waste Management – October 16, 2004 with 11 participants. 3. Organizational Meeting and Strategic Planning – December 11, 2003 with 47 participants. 4. Information Education Campaign (IEC) Training – March 18, 2004 with 63 participants. 5. Information Education Campaign (IEC) “House to House Campaign” – March 19, 2004 with 32 participants. 6. Collection Point Identification – March 24, 2004 with 25 participants. 7. Public Information (Posting of information on proper time of waste disposal – 2004. The Barangay formed Barangay Ecological Solid Waste Management Committee (BESWMC) and designated officials and point persons as mandated by ordinance no. 3, which include Punong Barangay as chairman, Baranagy Kagawad, SK Chairman, Homeowners Association president, school representative, Public School Parents-Teachers Association president and president or representative of Association of Business Community, as members. It established backyard composting at the household levels. The segregation at source was already practiced by 1506 households (51.921 % as of April 2005) of the Barangay. There were 22 collection points in ten (10) Puroks. It also established material recovery facility (MRF) at Purok 9, San Rafael Urban Poor Area. The recovered recyclables were collected and sold. Some of these recyclables were used to form other products. There were about 150 kilos of recyclables collected per month. It created solid waste characterization in which it would the basis for segregation, collection and recycling. CENRO – Basura Patrol was formed to inspect and evaluate garbage as part of the Mandatory Waste Segregation and for proper monitoring. The Barangay always encouraged residents to participate in all SWM programs. Some of them were designated point persons and allowed to attend trainings and seminars. Continuing SWM Program. The Barangay had made its SWM program continuing as manifested in the monthly CENRO monitoring reports. The violators of the ordinances were correspondingly penalized. Validity of SWM Evaluation Instrument. The SWM self-evaluation made by Barangay 9-A had been validated as per respondents’ views and comments. Barangay 9-A got more than the required merit points as per evaluation of the city validation team.

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Efficacy of the SWM Evaluation Instrument. Based on the above indicators and manifestations, the SWM evaluation instrument is effective and useful tool in the implementation of Barangay SWM programs as mandated by RA 9003. It established a standard in evaluating SWM programs. CONCLUSIONS

The following conclusions are drawn from the above findings: 1. Barangay 9-A substantially adhered to the criteria set; 2. The Barangay passed necessary ordinances on SWM, conducted environmental education, designated officials, established composting and recycling activities and point persons to monitor the programs, and encouraged social participation; 3. The SWM programs of the Barangay are continuing; 4. The SWM self-evaluation had been validated as per respondents’ views and comments and evaluation by the city validation team; and 5. The SWM evaluation instrument is effective and useful. ACKNOWLEDGEMENTS The proponents of this study are grateful to the following persons for their support and assistance: Honorable Juanito O. Apale, Jr., Chairman of Barangay 9-A, Dr. Ma. Linda B. Arquiza, University of Mindanao Research Director, Engr. Maria Esther Consuelo C. Tan, UM College of Engineering Research Coordinator and Ms. Gina Israel, consultant of this study. REFERENCES 1. Chan Robles Virtual Law Library. (2006). Available: http://www.chanrobles.com/republicactno9003.htm# ECOLOGICAL%20SOLID %20WASTE%20MANAGEMENT%20ACT%20OF%202000 [October 26, 2006] 2. http://www.sunstar.com.ph/static/ilo/2005/12/11/news/environment.presents.ra.90 03.html [October 26, 2006]

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COMPARISON OF DIFFERENT TYPES OF COATINGS IN HEADSPACE SOLID PHASE MICROEXTRACTION FOR THE ANALYSIS OF PESTICIDE RESIDUES IN VEGETABLES AND FRUITS Chai Mee Kin1 and Tan Guan Huat2 1

Dept. of Science and Mathematics, College of Engineering, Universiti Tenaga Nasional, Km 7, Jalan Kajang-Puchong, 43009 Kajang, Selangor. [email protected] Fax:03-89263506 2

Dept. of Chemistry, Faculty of Science, Universiti Malaya, Lembah Pantai, 50603 Kuala Lumpur.

ABSTRACT Despite the continuing development of solid-phase microextraction (SPME) fiber coatings, their selection presents some difficulties for analytes in choosing the appropriate fiber for a particular application. There are many types of SPME coatings available commercially. The most widely used for determination of pesticide residues in vegetable and fruits are polydimethylsiloxane (PDMS) and polyacrylate (PA). A headspace solid phase microextraction (HS-SPME) procedure using these two commercialized fibers (PDMS and PA) is presented for the determination of selected groups of organochlorine and organophosphorus pesticides. The extraction performances of these compounds were compared using these two fibers. The optimal experimental procedures for the adsorption and desorption of pesticides were determined. An explanation for the extraction differences is suggested based on the different thickness, polarity of the polymeric film of fibers and the different extracting matrices. In addition, the higher detector response of the pesticides after addition of aliquots of water and an organic solvent to the vegetable and fruit samples are also discussed. The SPME fibers were re-usable until a maximum of 120 extractions. Finally, the optimized procedures were applied successfully for the determination of these compounds in vegetable and fruits samples. Mean recoveries for all pesticides were between 75.0-97% with RSD below 7%. Keywords: HS-SPME, GC-ECD, GC-MS, pesticide. INTRODUCTION The current developments of analytical technologies to detect pesticide residues in fruits and vegetables have mostly focused on the simplification, miniaturization and improvement of the sample extraction and cleanup methods with universal microextraction procedures [1]. Solid-phase microextraction (SPME), developed by Pawliszyn and co-workers and has been marketed since 1993 by Supelco in an attempt to redress limitations inherent in SPE and LLE [2]. It can integrate sampling, extraction, concentration and sample introduction into a single uninterrupted process, resulting in high sample throughput. Its important features are its simplicity, low cost, rapidity, selectivity and sensitivity. SPME has been applied to analysis in various 10

fields, such as environmental chemistry, forensic chemistry, pharmaceutical, food, beverage and flavours. [3-6]. Nowadays, a large number of fiber coatings are available, namely poly dimethlysiloxane (PDMS), polyacrylate (PA), PDMS-divinylbenzene (DVB), carbowax-DVB, Carboxen-PDMS and DVB-Carboxen-PDMS coated fibers. However, the majority of studies concerning the determination of pesticide residues are performed using manual SPME, PDMS or PA fiber, and direct immersion. [7-11]. Although direct SPME applications for the determination of pesticides in food samples such as juices [12], honey [5,10] and fruit samples [1] have been reported, only a few references on the headspace (HS) SPME approach for the determination of pesticides in fruit [13-14] or vegetable [15-16] samples can be found. The present study was carried out to evaluate two different fibers, PDMS and PA in the extraction of 8 organophosphorus and organochlorine pesticides in fruit and vegetable samples using HS-SPME. EXPERIMENTAL Chemicals and Reagents All solvents used were HPLC grade. Pesticide standards (diazinon, chlorothalonil, malathion, chlorpyrifos, quinalphos, profenofos, -endosulfan, -endosulfan) were > 95% pure and obtained from AccuStandard Inc. New Haven CT, USA. Stock standard solutions of each pesticide at different concentration level, 5-400 mg/kg were prepared in methanol and stored at 4 oC. Working standard solutions of pesticides mixture were prepared daily by volume dilution in distilled water. In the calibration and quantitation studies, an internal standard, 1-chloro-4-fluorobenzene, 200 g/L which is effective as a surrogate to compensate the data of all the 8 pesticides was added to each sample prior to GC analysis. SPME Procedure SPME holder and fiber assemblies for manual sampling were obtained from Supelco (Bellefonte, PA, USA) and used without modification. The fiber coatings assayed were polydimethylsiloxane (PDMS 100 m) and polyacrylate (PA 85 m). Before measurements the PDMD fiber was conditioned in the injector to fully remove any contaminant which may cause high baseline noise and large ghost peaks. Then the fibers were repeatedly injected into the GC until the interfering peaks disappeared. Preliminary experiments were carried out to evaluate the HS-SPME process by comparing two coating materials with different polarities and thickness. After that, the optimization of the main parameters affecting the SPME of the pesticides from aqueous solution (i.e. extraction time and temperature, desorption time and temperature, the effect of salt addition and stirring rate) were carried out. In these studies, distilled water samples spiked with the appropriate amount of the standard solution was used. In contrast, the spiked vegetable and fruit samples were used for the study of the effects of dilution and organic solvent.

Fruit and Vegetable Samples All determinations were performed using the PDMS 100 m fibers. Initially, 1.0 g of the homogenized fruit and vegetable sample was placed in a 15 mL clear glass vial and added with 100 L of a mixture of methanol/acetone (1:1), and topped up with 11

distilled water containing 10% NaCl to 5.0 g. The samples were added with the internal standard. The PDMS fiber was exposed to the headspace above the sample for 30 min at 60 oC. Quantification of pesticides in the samples was carried out by a five point-calibration in the matrix using spiked samples by comparing the ratio the peak area of the analyte against the peak area of the internal standard versus the concentration of the analytes. Each sample was analyzed in triplicates. Blanks were run periodically during the analysis to ascertain the absence of any contaminant pesticides. Gas Chromatography – Electron Capture Detector (GC-ECD) A Shimadzu GC 17A version 2.21 gas chromatograph with an electron capture detector (ECD) was used. A SGE BPX5, 30m x 0.32 mm id capillary column with a 0.25 m film was used in combination with the following oven temperature program: initial temperature 120 oC, then heated at 7 oC/min to a final temperature of 250 oC, and then held for 4.5 min. The total run time was 23.07 min. The splitless mode was used for the injection. The injector temperature was at 240 oC and the detector temperature was at 300 oC. Nitrogen gas (99.999%) was used as the carrier gas with a gas flow at 24.4 cm/sec linear velocity and the pressure at 94 kPa. RESULTS AND DISCUSSION Selection of SPME coating The choice of an appropriate coating is essential for the SPME method. The sensitivity of each fiber is different depending on the molecular mass and the polarity of the analytes to be extracted. The performance of PDMS and PA were compared by determining the detector response (peak area) of the selected OCPs and OPPs insecticides. Table 1: Physicochemical properties of the selected pesticides molecular formula, molecular weight, water solubility, vapor pressure and Log Kow 17 Name

Molecular Formula Diazinon C12H21N2O3PS Chlorothalonil C8Cl4N2 Malathion C10H19O6PS2 Chlorpyrifos C9H11Cl3NO3PS Quinalphos C12H15O3N2PS Profenofos C11H15BrClO3PS -Endosulfan C9H6Cl6O3S -Endosulfan C9H6Cl6O3S

Molecular Weight 304.35 265.92 330.36 350.62 298.18 373.60 406.96 406.96

Water Solubility (mg/L) at 25 oC 40 0.6-1.2 130 2 22 28 0.32 0.32

Vapor Pressure (mm Hg) 9.02 x 10-5 5.7 x 10-7 3.94 x 10-5 2.02 x 10-5 2.6 x 10-6 6.23 x 10-6 3.0 x 10-6 5.96 x 10-7

From Table 1 and Table 2, it was observed that compounds with the higher octanolwater partition coefficient (log Kow) and low solubilities in water, such as chlorpyrifos, -endosulfan and -endosulfan were the more extensively adsorbed when the PDMS fiber is used due to the higher affinity to the non-polar fiber coating. In contrast, when the PA fiber is used the less polar insecticides were less effectively 12

Log Kow 3.30 3.05 2.75 4.69 4.44 4.74 3.83 3.83

extracted with a decrease adsorbed amount of 20-30 % when compared to PDMS fiber. Compounds with higher polarities such as malathion and diazinon were adsorbed at a higher percentage (65-80%) by PA in relation to PDMS fiber. Generally, the PDMS fiber gives high extraction efficiency than the PA fiber which can be explained not only by the nature of the fiber or compounds, but by the slightly larger volume of the PDMS fiber with respect to the others and hence the larger capacity to adsorb the analytes. -Endosulfan presents the best limit of detection due to the high ECD response as a consequence of having six chlorine atoms in its molecule. Table 2: Mixture concentration, detector response and LOD of the selected pesticides. Compounds

Diazinon Chlorothalonil Malathion Chlorpyrifos Quinalphos Alpha-Endo Profenofos Beta-Endo

Mixture Conc. (g/L) 160 80 160 4 160 2 20 4

PA Peak Area 51600 20910 32350 213738 29911 150010 28592 109042

LOD (ng/L) 50 50 100 5 100 1 5 5

PDMS Peak LOD Area (ng/L) 77855 10 59586 10 40677 50 813108 1 43403 50 695171 0.2 53532 1 419156 1

Peak Area ( PA x 100%) PDMS

66.28 35.09 79.53 26.29 68.92 21.58 53.41 26.01

Parameters influencing the HS-SPME process HS-SPME is an equilibrium process that involves the partitioning of analytes from aqueous phase to gas phase and eventually into the polymeric phase according to their partition coefficients Kd [2]. The optimization of parameters that influence the partition of analytes between the headspace and the solution are thus extremely important. Temperature, appropriate time period for the extraction, memory effect, stirring rate and ionic strength are the main parameters that should be taken into account. The optimization of above parameters was checked with both types of fibers. Effects of Extraction Temperature Extraction temperature should be optimized first since it plays the most important role in the extraction process by controlling the diffusion rate of analytes into the coating. The effect of temperature in the extraction yield was investigated by varying the temperature between room temperature (25 oC) and 95 oC with a constant extraction time of 30 min. In relation to the expected behavior of the pesticides, increasing the temperature improves the mobility of the pesticides through the liquid and gas phase and better recoveries were obtained up to 60 oC. At higher temperatures the ability of the SPME fiber to adsorb the tested pesticides begins to decrease. This is because adsorption is an exothermic process and therefore, disfavored at high temperatures. Thus increasing the temperature would cause the distribution constant at equilibrium to decrease [18]. Moreover, the decrease of the extraction yield could be due to the enhanced hydrolysis of OPPs at elevated temperatures. Besides, an increase in water vapor 13

pressure is another cause of decrease in the sensitivity of HS-SPME when the extraction temperature exceeds 60 oC. Thus, the optimum extraction is achieved at 60 o C and this temperature was selected for the subsequent experiments. Effects of Extraction Time Since the HS-SPME technique is an equilibrium process of the analytes between the vapor phase and the fiber coating, it is important to determine the time required to reach equilibrium. When analytes have low values for Henry’s constant, low concentrations at the vapor pressure are expected, thus translating to a small concentration gradient and this results in longer periods to reach the equilibrium. Furthermore, analytes with high molecular masses are expected to require longer equilibrium times, due to their lower diffusion coefficients (the equilibrium time is inversely proportional to the diffusion coefficient) [19] Under the above observed optimum conditions, adsorption-time profiles for PDMS and PA fibers were generated for each pesticide and are presented in Figs. 1A and 1B, respectively. For the PDMS fiber, the equilibrium time of most analytes is shorter and almost reached after 60 min (Fig 1A), whereas, all the analytes need 90 min to reach equilibrium for PA fiber (Fig 1B). This is because PDMS coating is a viscous liquid polymer and the diffusion coefficient of the analyte in it will be orders of magnitude higher than its diffusion coefficient in a solid polymer of PA. Therefore, since the dynamics of mass transport in a well-stirred solution is controlled by the diffusion coefficient of analyte in the coating, the extraction time required with a liquid polymer coating will be considerably less than that required with a solid-phase polymer [2]. Thus the longer equilibrium time for the PA coating can be explained. Another limitation of PA for the extraction of organophosphorus and organochlorine pesticides is the more polar character of its coating. Extraction Tim e (PA)

40 30 20 10 0 5min

20min

40min 75min Time (min)

Diazinon

25 Peak Area (x10 5 )

P e a k A re a ( x 1 0 5 )

Extraction Time (PDMS) 50

105min

150min

Fig. 1A: Extraction Time of PDMS

Chlorothalonil

20

Malathion

15

Chlorpyrifos

10

`

Quinalphos

5

Alpha-Endo

0

Profenofos 5 min

20min

40min 75min Tim e (m in)

105min

150min

Beta-Endo

Fig. 1B: Extraction Time of PA

Effects of Stirring Rate The results showed that the response increases if the stirring speed is increased which agrees with the fact that SPME is a technique based on equilibrium and that good diffusion through the phases is essential to reach equilibrium faster. Although the equilibrium time progressively decreases with increasing agitation rate, the amount of analyte extracted decreases at the maximum speed. This is because at the maximum speed the stirring bar begins to vibrate and agitation of the sample is not uniform. This faster agitation tends to be uncontrollable and the rotational speed might cause a change in the equilibrium time and poor measurement precision. Thus, a constant gentle stirring speed was selected in this study to increase the rate of extraction. 14

Effects of Ionic Strength In SPME procedure the salting out effect can be employed to modify the matrix by adding a salt, e.g. NaCl to increase the ionic strength of the matrix so as to decrease the solubility of analytes and release more analyte into the headspace, thereby, contributing to enhanced adsorption on the fiber [19]. The increase in solubility of analtyes in water, will increase the influence on adsorption by the addition of a salt. Thus, with reference to the PDMS fiber the compounds with higher water solubility such as diazinon and malathion showed an increase in extraction yield by increasing the NaCl concentration until 30% (w/v). However, no effect or even a slight decrease in extraction yield was observed for compounds of low water solubility after 10% (w/v). For the PA fiber, similar behavior was observed. Salt contents of 10% were selected for the PDMS and PA fibers. Effects of Desorption Temperature In SPME techniques, a significant amount of the analytes often remain adsorbed on the fiber after the desorption step in the GC injection system. This problem becomes more serious when low volatility compounds are analyzed. For both fibers, desorption at 200 and 230 oC was not capable of desorbing completely the analytes; they were completely removed from the coating at 240 – 300 oC and not much significant differences were observed within this range of temperature. Hence a temperature of 240 oC for PDMS and 260 oC for PA were selected since high temperatures can shorten the coating lifetime and can result in the bleeding of the polymer, causing problems in the separation and quantification [20]. Effects of Desorption Time After investigating several desorption times between 1 to 15 min the results showed that a 6 minute-period was sufficient to desorb pesticides in the GC injector port; but the fiber remained for another 4 min to eliminate all residues on the fiber to guarantee a reproducible desorption. Effects of Water and Organic Solvent The influence of adding water on the samples in order to favor the release of analyte from the matrix was established by using different amounts of water. The results showed that the detection response of all pesticides was enhanced with the addition of water and decreased when the amount of water added exceeded a certain level. The HS-SPME process is affected by the suspended matter and dissolved compounds (sugar, pectins etc) contained in the vegetable and fruit samples which could adsorb the analytes, forming micelles and thus making it difficult for the analytes to reach the fiber (interfering with diffusion) [21]. Since the analytes were analyzed by HS-SPME, the addition of higher amounts of water would dilute the concentration of the analytes and increase the diffusion barrier of pesticides from aqueous phase to gaseous phase. Moreover, the increase or decrease in average recovery (%) obtained was compound and structure-dependent. The average recovery (%) of chlorpyrifos was significantly increased when the amount of water added reached the optimum level. This is because chlorpyrifos has low water solubility (2 mg/L) and high vapor pressure (2.02 x 10-5 mmHg). The desorbed pesticides will be easily released from aqueous solution to gaseous phase. However, malathion which has a relatively high water solubility (130 15

mg/L) and low vapor pressure (3.94 x 10-5 mmHg) to be released from the sample matrix will be retained in aqueous solution, and subsequently not much significant increase in the recovery (%) will be obtained when the amount of water added is increased. The addition of hydrophilic solvents can also promote the release of organic compounds from the vegetable and fruit samples. However, the presence of a high concentration of an organic solvent would lead to a significant decrease in the extraction efficiency of the analytes [21]. Therefore, only a small amount of solvent is recommended for use as the additive. In this study, 2% (vol/weight) of organic solvent was added to the vegetable and fruit samples. From the results obtained, an average percentage recovery (%) obtained using a mixture of methanol/acetone (1:1) was much higher compared to that using the other organic solvents. Besides the extraction efficiency, a mixture of methanol/acetone (1:1) was selected because it is relatively non-toxic, easy to volatilize and readily obtainable in the laboratory. Coating lifetime A coating lifetime is important for practical application (changes of efficiency with number of analyses). The coating is damaged mainly during the extraction due to interference between the matrix of samples and the fiber. This effect is more pronounced when the sampling is performed directly from the aqueous solution (immersion SPME). In contrast, in the HS-SPME mode the fiber is suspended in the headspace above the liquid layer of the samples and there is no interference between the matrix of samples and the coating. Thus the coating is protected and the lifetime is increased. In conventional SPME process (immersion technique) each fiber can be reused for approximately 30 times for surface water samples and 27 times in run-off water [18,22]. However, in this study using the headspace technique the fibers can be re-used for up to100 – 120 times. Recoveries Table 3: Recovery test on vegetable and fruit samples by using the optimized developed procedure. Pesticide

Diazinon Chlorothalonil Malathion Chlorpyrifos Quinalphos Alpha-Endo Profenofos Beta-Endo

Linear range (g/L) 1000-10 1000-10 5000-50 50-0.5 5000-50 20-0.1 100-1 100-1

LOD (g/L) 0.2 0.2 1.0 0.02 1.0 0.01 0.1 0.1

Tomato Recovery (n=3) 91  1.3 92  1.4 94  1.8 82  2.5 95  0.3 93  0.7 90  1.4 81  0.8

Guava (%) Recovery (n=3) 82  3.3 84  0.8 95  0.8 94  0.5 92  1.9 92  1.2 94  0.8 97  0.9

(%)

The addition of aliquots of water and organic solvent yielded extraction recoveries ranging between 75% and 97% for all the selected pesticides in all the vegetable and fruit samples studied. The relative standard deviations for all the experiments studied were less than 7% and linear calibration curves resulted for all the investigated range 16

with correlation coefficients better than 0.9900. Table 3 showed that the linear range, LOD, mean relative recoveries and RSD values by using the optimized HS-SPME procedure. This method also tested on actual vegetable (tomato) and fruit (guava) samples and it was found that the pesticide residues of these two types of samples were below the Maximum Residue Level as stated in the Malaysian Food Act 1983 which is from 1 to 50 g/L. CONCLUSION This comparative study of SPME procedures using different types of fibers showed that the use of these coatings is very useful for the determination of organophosphorus and organochlorine pesticides in fruit and vegetable samples. The differences in selectivity provided by the different coating can be used not only for quantification purposes, but also for identification of these compounds in complex matrices. Optimization of the parameters affecting the method sensitivity should be carefully developed in order to enable substantial increase in the amount extracted of most analytes and to improve the limit of detection. The developed method of HS-SPME with GC-ECD is precise, reproducible and linear over a wide range. ACKNOWLEDGEMENTS The authors acknowledge the financial support provided by the Malaysia Toray Science Foundation and Universiti Tenaga Nasional to pursue the research work. The authors would like to thank University of Malaya for providing the opportunity and facilities to undertake the research. REFERENCES 1. J. Beltran, F. J. Lopez, F. Hernandez, 2000, “Solid-phase microextraction in pesticide residues analysis”, J. of Chromatogr. A, 885, 389-404. 2. J. Pawliszyn, 1997, “Solid-phase microextraction: Theory and Practice” Wiley – VCH. 3. M. F. Alpendurada, 2000, “Solid-phase microextraction: a promising technique for sample preparation in environmental analysis – Review”, J. of Chromatogr. A, 889, 3-14. 4. M. Correia, C. D. Matos, A. Alves, 2000, “Multi-residue methodology for pesticide screening in wines”, J. of Chromatogr. A, 889, 59-67. 5. J. J. Jimenez, J. L. Bernal, M. J. del Nozal, 1998, “Solid-phase microextraction applied to the analysis of pesticide residues in honey using gas chromatography with electron capture detection”, J. of Chromatogr. A, 829, 269-277. 6. H. Kataoka, H. L. Lord, J. Pawliszyn, 2000, “Application of solid-phase microextraction in food analysis”, J. of Chromatogr. A, 880, 35-62. 7. J. Beltran, F. Hernandez, 2001, “Gas chromatography determination of organochlorine and organophosphorus pesticides in human fluids using solidphase microextraction”, Anal. Chim. Acta, 433, 217-226. 8. A. Sanusi, V. guillet, M. Montury, 2004, “Advanced method using microwaves and solid-phase microextraction coupled with gas chromatography-mass spectrometry for the determination of pyrethroid residues in strawberries”, J. of Chromatogr. A, 1046, 35-40.

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9. H. Berrada, G. Font, J. C. Molto, 2004, “Application of solid-phase microextraction for determination phenylurea herbicides and their homologous anilines from vegetables “, J. of Chromatogr. A, 1042, 9-14. 10. M. Fernandez, C. Padron, L. Marconi, S. Ghini, R. Colombo, A. G. Sabatini, 2001, “Determination of organophosphorus pesticides in honeybees after solidphase microextraction”, J. of Chromatogr. A, 922, 257-265. 11. M. Correia, C. D, Matos, A. Alves, 2001, “Development of a solid-phase microextraction gas chromatography electron capture detection methodology for selected pesticides in must and wine samples”, Fresenius J. Anal. Chem., 369, 647-651. 12. A. L. Simplicio, L. V. Boas, 1999, “Validation of a solid-phase microextraction method for the determination of organophosphorus pesticides in fruit and fruit juice”, J. of Chromatogr. A, 833, 35-42. 13. Y. I. Chen, Y. S. Su, J. F. Jen., 2002,“Determination of dichlorvos by on-line microwave-assisted extraction coupled to headspace solid-phase microextraction and gas chromatography electron capture detection”, J. of Chromatogr. A, 976, 349-355. 14. M. J. Gonzalez-Rodriguez, F. J. arreola-Liebanas, A. G. Frenich, J. L. MartinezVidal, F. J. Sanchez-Lopez, 2005, “Determination of oxadiazon residue by headspace solid-phase microextraction and gas chromatography-tandem mass spectrometry”, Anal. Bioanal. Chem., 382, 164-172. 15. M. M. Mazida, M. M Salleh, H. Osman, 2005, “Analysis of volatile aroma compounds of fresh chilli (capsicum annuum) during stages of maturity using solid-phase microextraction”, J. of food composition and analysis 18, 427-437. 16. C. Z. Dong, Z. R. Zeng, X. J. Li, 2005, “Determination of organochlorine pesticides and their metabolites in radish after headspace solid-phase microextraction using calix [4] arene fiber”, Talanta 66, 721-727. 17. M. Sakamoto, T. Tsutsumi, 2004, “Applicability of headspace solid-phase microextraction to the determination of multiclass pesticide in waters”, J. of Chromatogr. A, 1028, 63-74. 18. D. A. Lambropoulou, T. A. Albanis, 2001, “Optimization of headspace solidphase microextraction conditions for the determination of organophosphorus insecticides in natural waters”, J. of Chromatogr. A, 922, 243-255. 19. I. Bras, L. Santos, A. Alves, 2000, “Monitoring organochlorine pesticides from landfill leachates by gas chromatography-electron capture detection after solidphase microextraction”, J. of Chromatogr. A, 891, 305-311. 20. J. Beltran, A. Peruga, E. Pitarch, F. J. Lopez, F. Hernandez, 2003, “Application of solid-phase microextraction for the determination of pyrethroid residues in vegetables samples by gas chromatography-mass spectrometry”, Anal. Bioanal. Chem., 376, 502-511. 21. D. A. Lambropoulou, T. A. Albanis, 2003, “Headspace solid-phase microextraction in combination with gas chromatography – mass spectrometry for the rapid screening of organophosphorus insecticide residues in strawberries and cherries”, J. of Chromatogr. A, 993, 197-203 22. J. Dugay, C. Miege, M. C. Hennion, 1998, “Effect of the various parameters governing solid-phase microextraction for the trace-determination of pesticides in water”, J. of Chromatogr. A, 795, 27-42.

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DETERMINATION OF SOME HEAVY METALS IN BANGMOD CANAL BANGKOK G.Mathap1, B. Limchawfar1, S. Sujaritvanichpong2, S. Santikoon1, S. Chongcharoen1and R. Thanawadee2 1 Department of Chemistry, Faculty of sciences, KMUTT, Bangmod, Bangkok,Thailand, 10140 2 Department of Environmental Sciences, Faculty of sciences, RU, Bangkok, Thailand E-Mail. [email protected] ABSTRACT This research was to determine some heavy metal contamination in Bangmod canal in Bangkok, in the period between August, 2005 (the rainy season) and January, 2006 (the winter season) by the flame atomic absorption spectrophotometric technique. It was found that the contents of the heavy metals : chromium, cadmium, copper, manganese and lead on the water surface are 0.004 – 0.269, 0.001-0.053, 0.001-0.057, 0.010-0.704 and 0.002-0.387 mg/l, respectively and those at the mid-depth of the water are 0.003-0.143, 0.001-0.094, .001-0.070, 0.056-0.694 and 0.002-0.240 mg/l, respectively. This results shown that the contents of heavy metals (all except chromium and lead) from both seasons in the Bangmod canal fall within the standard limit of ground water from the Pollution Control Department. The chromium, cadmium and lead contents are slight above the standard, Limit. Keyword : Heavy metal, Bangmod canal, Chaopraya River INTRODUCTION The analysis of the amount of heavy metals in Bangmod Canal, Bangkok, was undertaken for six months between the high water period (rainy season) and the low water period (winter) from August, 2005 to January 2006. The heavy metals in question are cadmium, chromium, copper, manganese and lead. Bangmod Canal is one of the most important canals in the Jomthong district of Bangkok. Along the canal, there are many populated communities whose residents use water from the canal for their daily activities, e.g.,washing cooking utensils. The canal is connected to the Chaopraya River, one of Thailand’s major rivers. It is hoped that this study is helpful to endeavours undertaken to protect the environmental and living conditions of the people who live along the canal and might be affected by the heavy metal contamination of the water. METHODOLOGY - Instruments i Atomic absorption spectrophotometer (Perkin Elmer, model Analysis AA300) ii A microwave oven (Auton paar, model 576178) iii Water quality examination instrument (YSI, model 610-B version 2.5-8.16 iv Water collecting instrument (Niskin) - Water sampling and analysis i Water sampling Water samples were collected using the Niskin water collecting instrument at 11 stations along the Bangmod Canal. At each station, (see details in Figure 1 and Table1), two samples were collected: one from a depth of 1 meter below the surface, and the other from a depth of 1 meter above the canal bottom. 19

ii Water collection and examination The standard method, as described the Examination of Water and Wastewater 18th ed. (APHA, AWWA and WPCE, 1995), was employed in this study. RESULTS AND DISCUSSION -The results for the average concentration of the heavy metals in the high water season is shown in Table 1 and Figures 2. -The results for the low water season is shown in Table 2 and Figures 3 -The analysis of the average percentage of recovery of these heavy metals in the two seasons, at the five stations where one sample was collected, is shown in Table 3. CONCLUSIONS As indicated by the results of this study, the concentrations of each heavy metal, with the exception of manganese, in the Bangmod Canal during both seasons are approximately the same at the water surface and at the bottom of the canal. The concentration of manganese is higher than for the other metals, because manganese is widely used in the steel industry. Cadmium and copper were found to have the lowest concentrations. This might be due to the fact that these two metals are not major elements used in industry. The concentrations of heavy metals found in both seasons was inclined to be higher (see details in Figures 2). When investigating the R2 of these heavy metals during the two seasons between the two water surface and the canal bottom, it was found that there was no statistical significant relation between the dispersion rate of these heavy metals. Nevertheless, there was a higher deposit of heavy metals at the canal bottom than at the surface. The recommended measures to lower the concentrations of heavy metals and to improve the conditions of Bangmod Canal are as follows: configuring the natural sources and environmental data of the area along the canal using GIS; proactively managing and administrating the rehabilitation of the canal with the cooperation of the community; taking rolling plans and measures for solving the problems facing the canal, as well as initiating projects by government agencies to raise the awareness of the community in residing along the canal.

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REFERENCES: Availa-Perez P., Balcazar M., Zarazua-Ortega G., Barcelo-Quintal I. And Diaz –Delgado C., 1999, Heavy metal concentrations in water and bottom sediments of a mexican reservoir. Science of the total environment, 85-196 Eaton, D., et. al., 1995, Standard methods for the examination of water and wastewater 18th ed. (APHA, AWWA and PWCF). Dai, M., Martin, J. M., & Cauwet, G., 1995, The significant role of colloids in the transport and transformation of organic carbon and associated trace metals (Cd, Cu and Mn) in the Rhome delta (France). Mar. Chem., 51, 159-175. Horwits, W., 1969, Preparation of sample for atomic absorption spectrophotometry. J. Assoc. off Anal Chem. Vol. 52. Diagomanolin V., Farhang M., Ghazi-Khansari M. and Jafarzadeh N., 2004 Heavy metals (Ni, Cr, Cu) in the Karoon waterway river, Iran Toxicology Letters, Vol. 151, (1)15, 63-67 Hungespreugs, M., Dhaemvanij, S., Uttomprukpon, W., & Windon, H, L, 1990, A comparative study of the trace metal fluxes of the Bang Pakong and the Klong River, Thailand. The science of the Total Environmental, 97/98, 89-102. Laster, R., & Balls, P.W, 1995, The behavior of dissolved Mn, Ni and Zn in the Forth, on industrialized, Partially mixed estuary Mar. Chem., 48, 1979-1884 Mimoza Milovanovic, 2007, Water quality assessment and determination of pollution sources along the Axios/Vardar River, Southeastern Europe Desalination , Vol. 213, 1-3, 15 159-173

Figure 1: Sampling station

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Table 2: Content of heavy metals in rainy season Content of heavy metals (mg/l) station Cr Cd Cu Mn Pb surface bottom surface bottom surface bottom surface bottom surface bottom A1 0.122 0.204 ND 0.017 0.027 0.032 0.140 0.154 0.008 0.062 A2 ND 0.024 0.014 ND 0.015 0.028 0.010 0.119 ND 0.114 A3 0.117 0.097 0.010 0.094 ND 0.004 0.018 0.128 0.009 0.089 A4 0.145 0.124 ND 0.017 0.003 0.003 0.099 0.117 0.088 ND A5 ND 0.257 0.005 0.002 0.008 ND 0.100 0.124 0.036 ND A6 0.029 0.148 0.012 ND 0.010 ND 0.117 0.134 ND 0.116 A7 0.038 0.149 0.021 0.014 0.002 0.011 0.151 0.173 ND 0.122 A8 0.060 0.029 ND ND ND 0.052 0.123 0.123 0.066 ND A9 0.018 0.046 0.013 0.022 0.002 0.006 0.133 0.154 0.058 ND A10 0.083 0.193 0.006 0.007 0.001 0.020 0.165 0.132 ND 0.055 A11 0.023 0.161 0.014 0.015 0.011 0.016 0.208 0.192 0.151 0.027 ND = not detected

Table 3 Content of heavy metals in winter season Content of heavy metals (mg/l) Cr Cd Cu Mn Pb surface bottom surface bottom surface bottom surface bottom surface bottom A1 ND 0.017 0.001 0.027 0.027 0.001 0.053 0.053 ND ND A2 0.083 0.129 ND ND 0.044 ND 0.069 0.086 ND ND A3 0.256 0.171 0.006 0.003 ND 0.028 0.079 0.081 ND ND A4 0.108 0.030 ND ND ND ND 0.067 0.093 0.020 ND A5 0.004 0.144 ND ND 0.022 0.024 0.077 0.081 0.039 0.045 A6 0.049 0.003 0.031 ND 0.017 ND 0.072 0.076 0.076 0.036 A7 ND 0.126 ND ND ND ND 0.061 0.056 0.032 0.101 A8 ND ND 0.018 ND 0.002 0.070 0.076 0.074 0.079 0.022 A9 0.269 0.102 0.016 0.002 0.015 ND 0.087 0.074 ND ND A10 0.241 0.165 0.038 ND ND 0.042 0.061 0.077 0.052 0.029 A11 0.163 0.188 ND ND ND 0.033 0.116 0.137 0.151 0.105 ND = not detected station

Table 4: Average percentage of recovery heavy metals in two seasons heavy metals Content of heavy metals (% recovery) Cr 95.08 Cd 99.04 Cu 95.73 Mn 97.51 Pb 94.70

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Figures 2: Content of Cr (A) , Cd (B), Cu (C), Mn (D), Pb (E) between surface and bottom in rainy seasons A) B) 0.1 0.09 0.08

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A SURVEY ON ELECTRONIC WASTES AND THEIR DISPOSAL IN DAVAO CITY Jenith L. Banluta1, Johna Marie R. Tabanguil2, Evtri E. Tabanguil2, Albert Jubilo1 1

Engineering and Architecture Division, Ateneo De Davao University, Jacinto Street, Davao City 8000, Philippines; Cell No.+63829164038534; [email protected] 2 College of Engineering, University of Mindanao, Matina, Davao City 8000, Philippines; Cell No. +63829174958433; [email protected]

ABSTRACT The study is all about the electronic wastes and their disposal in Davao City, Philippines. Key words: Electronic wastes, disposal, toxic substances INTRODUCTION Electronic waste (E-waste) encompasses a broad and growing range of electronic devices ranging from personal computers and televisions, to handheld PDAs, VCRs, and cellular phones. The increasingly rapid evolution of technology has effectively rendered everything disposable. Then there are problems on these materials that affect the environment and human health. The major causes of growing E-waste volume are: (1) Replacement is often easier and cheaper than repair; (2) Obsolescence of electronics; and (3) Everimproving gadgets and new technologies and upgrades. The identified problems are: (1) Environmental and human health hazards; (2) Toxicity and managements cost is increasing; (3) E-wastes end up in the landfills. In the Philippines, there is an ever growing number of people who has access to these electronic equipment, more significantly of such materials are personal computers and mobile phones. The evolution of technology gives way to the emergence of cheap and readily available electronic goods which in turn, rapidly increases the generation rate of electronic waste (e-waste). Many components of these E-wastes contain heavy metals and toxic substances such as lead, mercury, cadmium, lithium, nickel, selenium, arsenic and many more. Some of these are carcinogenic substances. It is now our responsibility to minimize the impact of these E-wastes. As you can see, a lot of second-hand PCs and TVs sold in Davao City. There is a need to conduct a baseline study on these types of wastes. Research Problem. The purpose of this research is to study the electronic wastes in Davao City. Specifically, it sought to answer the following questions: (1) What are the different e-wastes handled and disposed by residential and commercial establishments in Davao City? (2) Are residential households aware of proper e-waste disposal?

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(3) How do residential households dispose their e-waste? (4) Is recycling practiced by residential households? (5) How do commercial establishments dispose obsolete electronic devices? It also seeks to create an e-waste material flow and propose an e-waste management program. Significance of the Study. The result of this study may be used as a basis to inform the citizens of the country, electronic device manufacturers, Department of Environment and Natural Resources, and the Department of Health. The results can also be used as a guide on how to implement means to solve the problem on e waste’s rapid escalation. Research Design. The proponents of this study used descriptive research design. Field observation was likewise used. Research Locale. The study was conducted in four administrative districts of Davao City: Agdao, Buhangin, Poblacion, and Matina. Research Instruments. Survey questionnaires and interview guide were used. Statistical Treatment. Percentage and mean were used in the study. RESULTS AND DISCUSSION The study was conducted from June 2006 to June 2007, wherein the field observation was initially sought. The commercial establishments and residents in the four districts were interviewed. After conducting the surveys the proponents of this study were able to come up with the following findings:  Majority of residential households are capable of purchasing electronic goods. Cellular phones comprise the major bulk of household electronic goods. The second largest is the category of battery chargers and adaptors. Television sets come in third. The rest of the categories are arranged in descending frequency: radio and stereo components, CD/DVD players, personal computers and laptops, storage devices, telephones, Betamax and VHS, MP3 Players, digital cameras, video cameras.  Residential households mainly dispose electronic products when the need arises.  Most residential households repair, sell, and donate malfunctioning and obsolete electronic goods. A portion of the respondents still resort to throwing, burning, and storing of these electronic products.  A good number of the residential households view recycling as an alternative way of electronic waste disposal.  Commercial establishments surveyed selling electronic products in the form of home appliances, computer parts & accessories, electronic parts, and electronic wires and cables do not practice recycling.

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CONCLUSIONS The following conclusions were drawn: (1) The electronic goods and/or products present in residential households are mobile or cellular telephones, battery chargers and/or adaptors, television sets, radio and/or stereo component systems, and Compact Discs and/or Digital Video Decoder players, respectively, with mobile phones as the most imminent form and CD/DVD players as the least. (2) Majority of residents have the basic knowledge on the proper disposal of electronic products due to the fact that a greater part of them read and follow stated directions on the disposal instruction labels of these products. (3) Most residential households prefer the selling and/or the repairing of electronic products. (4) Nearly every one considers recycling as an undeniable option in e-waste disposal although its practice is not exercised. (5) Recycling practices are not implored by commercial establishments.

ACKNOWLEDGEMENTS The proponents of this study are grateful to the following persons for their support and assistance: Dr. Randell U. Espina, chairperson, Engineering & Architecture Division, Ateneo De Davao University, and Dr. Ma. Linda B. Arquiza, Director, University of Mindanao Research Office, Engr. Ma. Consuelo Tan, UM College of Engineering Research coordinator, UM and AdDU faculty members, and validators. REFERENCES 1. California Against Wastes. (2006). Available: http://www.cawrecycles.org/issues/ewaste/poisonpc_exec_summary. [October 10, 2006] 2. E-Waste. (2006). Available: http://ewasteguide.info/facts_figures. [October 10, 2006]

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DEGRADATION AND LEACHING OF ACEPHATE AND CHLORPYRIFOS IN TROPICAL SOILS OF SARAWAK Lian-Kuet Chai1, Norhayati Mohd-Tahir2 & Hans Christian Bruun Hansen3 1

Agriculture Research Centre, Department of Agriculture Sarawak, 93720 Kuching, Sarawak, Malaysia 2 Faculty of Science and Technology, Universiti Terengganu Malaysia, Mengabang Telipot, 21030 Kuala Terengganu, Terengganu, Malaysia 3 Department of Natural Sciences, Faculty of Life Sciences, University of Copenhagen, Thorvaldsensvej 40, DK-1871, Frederiksberg C, Copenhagen, Denmark ABSTRACT The dissipation and mobility of acephate and chlorpyrifos have been studied in a red yellow podzolic soil (Paleudults), an alluvial soil (Udorthents) and a red yellow podzolic soil (Kandiudults) under field conditions in Sarawak. The aim of the study was to evaluate the degradation and leaching of acephate and chlorpyrifos as a result of its use to control pests in the soils after harvesting of vegetables. The method of acephate and chlorpyrifos application to the soils and its concentration used simulated the field situation. The results showed that the rate of acephate and chlorpyrifos degradation and migration varied among the soils and that local climatic conditions were important. Acephate degraded rapidly in soil compared to chlorpyrifos which was much more persistent. Shorter first-order half lives of 0.5 – 3.3 days were obtained for acephate in soils compared to 8.7 – 17.3 days for chlorpyrifos. Rainfall accelerated the acephate dissipation but had less effect on chlorpyrifos. Both pesticides could be detected in the subsoils at contents up to 3.2 mg/kg even 2 hours after application to the soil surface. Both pesticides were detected at 50 cm depth which was the deepest layer examined. Acephate probably leached via soil solution while chlorpyrifos may have migrated with soil particles moving through macro pores and cracks. Pesticides in the subsoils dissipated at similar rates as seen for the top soils demonstrating that subsoils harbour the necessary microorganisms for degradation of the pesticides. Higher amounts and intensity of sunlight accelerated the pesticide degradation in the top soils and thus conditions with much smog (haze) resulted in higher pesticide contents in top soils. INTRODUCTIONS Pesticides are used intensively by vegetable farmers to control pests in soils. They are often applied to the soils and crop residues after a vegetable crop has been harvested and before the next crop as a preventive treatment. As limited land is available for farming, many farms have been used for vegetable farming without fallowing. As a result, proliferation and buildup of pests in soils may occur. To overcome this problem, pesticide is applied to the soil one to two weeks before planting of a new crop. The drawbacks of this practice are the increasing risks of pesticide contamination of soil and water, and the effects of pesticides may have on non-target organisms. Furthermore, if the pesticides persist for longer times in the soil, it may be taken up by new crops. To date, there is very few information available on the

28

environmental fate of pesticides in tropical environments as a consequence of this practice. Relatively few data have been reported on pesticide fate under tropical climate conditions (reviewed by Racke et al., 1997). Laabs et al. (2000) reported short field dissipation half-lives of pesticides (t0.5 < 15 d) and a moderate leaching of polar herbicides to the subsoil in selected Brazilian soils. In another study, Laabs et al. (2002) reported rapid dissipation of pesticides in the field with half-lives of less than 20 days and rapid transportation of pesticides to 40 cm soil depth by preferential flow regardless of their sorption properties. Ngan et al. (2005) reported the half-lives for chlorothalonil, chlorpyrifos and profenofos was less than two days in soils used for vegetables in Malaysia. In another study, half-lives of 7 to 22 days were reported for dimethoate, monocrotophos, triazophos, deltamethrin, cypermethrin and endosulfan in cotton crop soils (Vig et al., 2001). None of the pesticides except endosulfan leached beyond 15 cm. Kathpal et al. (1997) reported the half-lives for endosulfan in cotton soil ranged from 39 to 42 days. The endosulfan and isomers could not be detected beyond 10 cm. The aim of the present investigation was to compare the degradation and mobility of the two organophosphorus pesticides, chlorpyrifos and acephate in three tropical soils (Kandiudults, Paleudult, Udorthents) in Sarawak simulating the situation where pesticides are sprayed onto the soils after harvesting of vegetables. RESULTS Soil Physiochemical Properties The physiochemical properties of the three soils studied are shown in Table 1. The three soils were all acidic with high clay contents in the subsoils. The carbon contents in the top soils were all higher than 1.5 % (w/w); also the subsoils were relatively high in organic carbon except for the Balai Ringin soil. The cation exchange capacity at pH 7 (CEC7) was relatively high for all the horizons of Semongok and Tarat soil. However, the CEC7 was lower for all horizons even for the very clayey subsoil horizons of the Balai Ringin soil demonstrating that this soil is rather weathered and is dominated by clay minerals with low CECs, e.g. kaolinite. The base saturation decreased with depth for all three soils reflecting the decrease in pH. The base saturation was highest for the least weathered Tarat soil. The content of aluminum oxide found in all horizons of Semongok and Tarat soils were high and increasing with soil depth. Similar trends were observed for the distribution of iron oxide. Table 1. Physicochemical properties of soils at different depths

Horizon pH (0.01 M CaCl2) % carbon % clay % silt % fine sand

Semongok soil 0-20 20-50 cm cm

Tarat soil 0-5 cm

5-35 cm

35-50 cm

0-12 cm

OA 4.8

B 4.5

OA 5.6

A 5.2

B1 5.1

2.20 23.1 29.6 9.8

0.92 34.2 20.5 6.4

1.78 13.9 15.4 44.1

1.43 37.2 18.0 23.1

0.88 41.6 13.3 26.1

29

Balai Ringin soil

OA 5.6

1220 cm A 4.8

2030 cm A 4.3

3050 cm B1 4.1

1.42 5.9 16.4 27.9

0.35 11.4 15.2 26.1

0.22 21.8 12.9 26.8

0.26 48.8 12.8 16.4

% coarse sand CEC7 (cmol(+)/kg) % base saturation Al oxides (mmol/kg) Fe oxides (mmol/kg)

37.6

30.6

26.6

21.8

19.1

49.9

47.3

38.6

22.0

11.8

12.1

16.2

16.2

14.4

5.0

5.0

5.9

8.1

40

15

70

53

47

88

34

29

21

56.4

78.9

63.0

98.5

155.2

12.0

7.5

12.5

19.2

196. 5

238.6

117. 7

143. 1

167.3

29.1

21.7

32.6

55.0

Pesticide distribution, migration and degradation Acephate. The top soil concentrations of acephate at day 0 were 5 – 6 times higher for Tarat and Semongok soils compared to the Balai Ringin soil (Figure 1). Acephate was present in the top 0 - 10 cm of the three soils throughout the sampling period, and concentrations declined almost exponentially with time. The acephate in the range of 0.01 to 2.24 mg/kg could be detected in the subsoils until the 50 cm which was the deepest soil layer examined. Acephate was observed in the subsoil already at 2 hours after spraying. The highest acephate subsoil concentrations were observed in the Tarat and Semongok soils where also the highest acephate concentrations in the 0 – 10 cm layer were observed. Acephate dissipated more rapidly in Tarat and Semongok soils compared to Balai Ringin soil. Results indicated that 97 - 98.5 % of the initial acephate concentration had dissipated from the Tarat and Semongok soils by day 2 compared to Balai Ringin soil where only 40 % has dissipated from the 0 – 10 cm layer by day 2. Acephate disappeared completely from Balai Ringin soil at day 21 compared to 7 days for the Tarat and Semongok soils. In the subsoils, acephate dissipated completely from the Balai Ringin soil at day 17, and after 7 and 4 days for the Tarat and Semongok subsoils, respectively. 0-10 cm 10-20 cm

5

20-30 cm 30-50 cm

4 3 2 1 0

10-20 cm 20-30 cm

25

30-50 cm

20 15 10 5 0

0

2

7

10 14 Time (days)

17

0

21

35

10-20 cm

30

20-30 cm

25

30-50 cm

20 15 10 5 0 0

2

4

2

4

Tim e (days)

0-10 cm

C

Content (mg/kg)

0-10 cm

B 30 Content (mg/kg)

Content (mg/kg)

A 6

7

Tim e (days)

30

7

Figure 1. Distribution of acephate in Balai Ringin (A), Tarat (B) and Semongok (C) soil profiles versus time. Vertical bars represent standard deviation (n = 3). Chlorpyrifos. The concentrations of chlorpyrifos in the top soils at day 0 were 3 – 5 times higher for the Tarat and Semongok soils compared with the Balai Ringin soil; the same pattern as seen for acephate (Figure 2). The chlorpyrifos contents in the three soils declined as the sampling time prolonged and also as the soil depth increased. Similar to acephate, chlorpyrifos could be detected in the subsoils. The Tarat soil showed the highest subsoil contents of chlorpyrifos in the range of 0.01 to 3.2 mg/kg. For all profiles, chlorpyrifos could be detected until a depth of 50 cm which was the deepest soil layer examined. Similar to acephate, chlorpyrifos appeared in the subsoil at depths up to 50 cm, two hours after it was applied to the soil. Chlorpyrifos was more persistent in the three soils and the rate of its degradation was slower compared to acephate. However, chlorpyrifos degradation was faster during the initial phase in the Balai Ringin and Semongok soils compared to the Tarat soil. By day 14, 56 % and 46 % of the chlorpyrifos had dissipated from the Balai Ringin and Semongok soils compared to 79 % in Tarat soil. The rate of degradation was gradual thereafter. The chlorpyrifos residue dissipated completely at day 98 in the three soils. Chlorpyrifos was present in the 10 – 50 cm layer of the Balai Ringin soil from day 0 to day 42 and steadily declined during the period. The Tarat soil showed the highest subsoil contents of chlorpyrifos in the three profiles and it vanished completely on day 98. There was surge in the chlorpyrifos concentration at day 21 in Tarat soil due to the occurrence of rainfall before the soil sampling. The chlorpyrifos concentration dip and surge more frequently in Semongok soils due to more rainfall events. The chlorpyrifos concentration dip sharply at day 4 and 14 but surge at day 7 and 21. The trend of chlorpyrifos concentrations in the Semongok soil was similar to that observed for Tarat soils. Chlorpyrifos dissipated completely from the 10 – 50 cm layer of Semongok soil by day 56. A

B

10-20 cm 20-30 cm

4

30-50 cm

3 2 1 0

0-10 cm 10-20 cm

16 Content (m g/kg)

5 Content (m g/kg)

0-10 cm

20-30 cm

12

30-50 cm

8 4 0

0

7

14 21 28 35 42 49 56 70 84

0

4

7 14 21 28 35 42 49 56 70 84 Time (days)

Time (days)

31

C ontent (m g/kg)

0-10 cm

C

10

10-20 cm 20-30 cm

8

30-50 cm

6 4 2 0 0

4

7 14 21 28 35 49 56 70 84 Time (days)

Figure 2. Distribution of chlorpyrifos in Balai Ringin (A), Tarat (B) and Semongok (C) soil profiles versus time. Vertical bars indicate standard deviations (n = 3) Degradation rate constants, half-lives and regression coefficients The degradation kinetic of the two pesticides was fitted with first-order kinetics and the fitting parameters are shown in Table 2. Regression coefficients (r2) were better than 0.73. The half-lives for acephate in the three soils ranged from 0.5 – 3.3 days. The shorter half-lives for Tarat and Semongok soils correlated with more rainfall during the experimental period at these two sites. For Chlorpyrifos, the half-lives obtained for the three soils ranged from 8.7 - 17.3 days. Despite regular and heavy rainfall at Tarat and Semongok, the half-lives were longer at these sites than at Balai Ringin in contrast to what was observed for acephate. The longer persistence for the Tarat and Semongok soils correlated with a higher content of organic matter at these sites than at the Balai Ringin site. Table 2. First-order degradation rate constants (k), half-lives (t1/2), and regression coefficients (r2) for acephate and chlorpyrifos in top soil material (0 – 10 cm) Pesticide

Acephate Chlorpyrifos Acephate Chlorpyrifos Acephate Chlorpyrifos

Regression coefficient, r2

Rate constant, k (days-1)

Balai Ringin soil 0.98 0.21 0.95 0.08 Tarat soil 0.73 0.98 0.85 0.04 Semongok soil 0.99 1.49 0.77 0.05

Half-life, t1/2 (day) 3.3 8.7 0.7 17.3 0.5 13.9

DISCUSSION Acephate. Acephate dissipated rapidly from the 0 - 10 cm of the three soils investigated and its disappearance was faster in Tarat and Semongok soils compared to the Balai Ringin soil. Hence, acephate degraded completely from the Balai Ringin soil in 21 days compared to 7 days for Tarat and Semongok soils. High precipitation 32

at Tarat and Semongok may have accelerated the acephate degradation. In addition, acephate is highly hydrophilic (790 g/l) and it has a low sorption affinity for organic matter (log Koc 0.48). Hence, heavy rainfall may have caused acephate leaching out of the soil profile beyond 50 cm. The amount of precipitation and its occurrence at the three experimental sites differed greatly. Less precipitation was recorded at the Balai Ringin site. The first major rainfall of 22.5 mm occurred on day 17 when the acephate concentration was already low. On the contrary, high rainfall occurred at Tarat and Semongok and it also occurred close to the day 0 when the acephate concentrations were at its highest; high rainfall occurred on day 2 (55 mm) and day 1 (61 mm) at Tarat and Semongok, respectively. In other studies, acephate has been reported to dissipate rapidly in both aerobic and anaerobic soils. Most of the applied acephate and its metabolite, methamidophos, degrade to immobile compounds in 20 days (Worthing & Hance, 1997; Thomson, 1982). It was reported the field half-lives for acephate in soil were 7-10 days for temperate soil (Tomlin, 1994). In laboratory studies, the half-lives reported for acephate were 7 to 20 days (30 0C) depending on the type of soils used (Yen et al., 2000). Acephate was detected in the three subsoils even two hours after its application to the soil surface. As there was no rainfall on day 0 at the three sites, the presence of acephate in the subsoil may due to migration through macro pores or cracks. From the pit profiling studies, it was found that there were many macro pores and cracks present in the three soil profiles. These pores and cracks could facilitate the pesticide leaching. Laabs et al. (2002) reported pesticide migration to the subsoil of 40 cm due to preferential flow. In the subsoil, the concentrations of acephate declined gradually as the depth increased. At longer sampling times, acephate could no longer be detected in the subsoil demonstrating that acephate also degrades relatively fast in the subsoils. The downward movement of acephate was more pronounced when the concentration in the top soils were higher. A similar trend has been reported by Konda & Pasztor (2001). Chlorpyrifos. Chlorpyrifos degraded gradually in the three soils investigated and was much more persistent in the top- and subsoils than seen for acephate. The chlorpyrifos degraded completely in the three soils within 98 days. The dissipation of chlorpyrifos was not much affected by precipitation despite high amounts of precipitation of 1130 and 1575 mm at Tarat and Semongok during the experimental period. Also the rainfall occurred closed to day 0, when the contents of chlorpyrifos in the top soils were high. Compared with acephate, chlorpyrifos is much more hydrophobic, i.e. it has a low water solubility and a high octanol-water partitioning coefficient (log Kow 4.7), and it has a high tendency to adsorb to soil organic matter (Wauchope et al., 1992; Racke, 1993). For non-tropical soils, the reported half-lives of chlorpyrifos varied widely and ranged from 2 to 145 days from various studies (Racke, 1993). Chlorpyrifos half-lives of 0.6 - 1.1 days were reported for tropical soils, depending on the soil properties and climatic conditions (Laabs et al., 2000; 2002). Chlorpyrifos appeared in the subsoil, two hours after application to the soil. As there was no rainfall on day 0 at the three sites, the occurrence of chlorpyrifos in the subsoil may due to migration through macro pores or cracks. The low solubility of chlorpyrifos makes migration with particulate matter more likely than transport in solution. The leaching of chlorpyrifos through pores and cracks concurred with the findings of Laabs et al. (2002), who reported that chlorpyrifos was transported to the

33

subsoil of 40 cm due to preferential flow. The Tarat soil showed the highest subsoil contents of chlorpyrifos correlating with the high top soil contents seen for this profile. Konda & Pasztor (2001) also reported significant vertical downward movement of chlorpyrifos in sandy loam of temperate soil during and immediately after rainfall and was more pronounced when the concentration in the top soils were higher. There were consistent anomalous dips and rises in chlorpyrifos concentrations in the top soils at days 4, 21 and 7 for the Tarat and Semongok soils (Figure 2). These dips and rises coincided with the occurrences of rainfall events. Similar observations have been presented by Rice et al. (2002). A possible explanation for these apparent losses and then recoveries back into the top layer of the soil was that the surface applied chlorpyrifos first leached below the sampling depth and then migrated back up into the surface layer when water evaporation from the soil surface started after the rain event, [i.e. the so-called “wick effect” (Taylor et al., 1995)]. However, the low solubility of chlorpyrifos is an argument against this hypothesis. Photodegradation and effect of haze (smog) Photodegradation and volatilization of acephate was likely to be most pronounced for the Balai Ringin soil as acephate was applied during noon time when the sunshine and sunlight intensities were high. The average daily sunshine on that day was 6.65. This has resulted in lower initial acephate concentration of 5.42 mg/kg detected in the 0 10 cm layer of Balai Ringin soil at day 0, two hours after it was applied to the soil. Acephate was also applied to the Tarat soil during noon time. However, due to haze (heavy smog) present, the amount of sunlight (1.45 h) and its intensity reaching the soil surface was substantially lower and thus strongly retarded the acephate photo degradation. Therefore, higher initial acephate concentration of 28.10 mg/kg was found in top 0-10 cm layer of Tarat soil at day 0. Photodegradation and volatilization is one of the most important factors for pesticide degradation in soils (Qin et al., 2006). Similar high initial acephate concentration of 31.8 mg/kg was found in the Semongok soil, and also at this site, sunlight was relatively low (2.6 h) and sun intensity lower due to haze on the day of application. Like acephate, photodegradation and volatilization of chlorpyrifos was most pronounced in Balai Ringin soil due to higher amount of sunshine and higher sunlight intensity. This has resulted in lower initial chlorpyrifos concentration of 4.4 mg/kg found in 0-10 cm layer of Balai Ringin soil, while, higher initial chlorpyrifos concentrations of 15.1 mg/kg and 9.3 mg/kg was found in top 0-10 cm layer of Tarat and Semongok soil at day 0. CONCLUSION Small amounts of the two pesticides as found to migrate into the subsoils, acephate probably via soil solution and chlorpyrifos via particulate transport through macro pores and cracks. The amount and intensity of the sunlight played a crucial role in the photo degradation and volatilization of the pesticides in the top soils. Acephate degraded rapidly in all soils. The half-lives of acephate for different soils were 0.5 – 3.3 days. Chlorpyrifos was much more persistent in soils and dissipated gradually in three soils. The half-lives for chlorpyrifos in different soils were 8.7-17.3 days.

34

REFERENCES 1. Kathpal, T.S., Singh, A., Dhankhar, J.S. & Singh, G. (1997) Fate of endosulfan in cotton soil under sub-tropical conditions of northern India. Pest. Sci., 50, 21-27 2. Konda, L.N. and Pasztor, Z. (2001) Environmental distribution of acetochlor, atrazine, chlorpyrifos and propisochlor under field conditions. J. Agric. Food Chem., 49, 3859-3863 3. Laabs, V., Amelung, W., Pinto, A. and Zech, W. (2002) Fate of pesticides in tropical soils of Brazil under field conditions. J. Environ. Qual., 31, 256-268 4. Laabs, V., Amelung, W., Pinto, A., Altstaedt, A. and Zech, W. (2000) Leaching and degradation of corn and soybean pesticides in Oxisol of Brazilian Cerrados. Chemosphere, 41, 1441-1449 5. Ngan, C.K., Cheah, U.B., Abdullah, W.Y.W., Lim, K.P. & Ismail, B.S. (2005) Fate of chlorothalonil, chlorpyrifos and profenophos in a vegetable farm in Cameron highlands of Malaysia. Water, air and soil pollution : Focus, 5, 125136 6. Qin, S., Budd, R., Bondarenko, S., Liu, W. and Gan, J. (2006) Enantioselective degradation and chiral stability of pyrethroid in soil and sediment. J. Agric. Food. Chem., 54, 5040-5045 7. Racke, K.D. (1993) Environmental fate of chlorpyrifos. Rev. Environ. Contam. Toxicol. 131: 1-151 8. Racke, K.D., Skidmore, M.D., Hamilton, D.J., Unsworth, J.B., Miyamoto, J. and Cohen. S. Z. (1997) Pesticide fate in tropical soils. Pure Appl. Chem. 69, 1349-1371 9. Rice, C.P., Nochetto, C. B. and Zara, P. (2002) Volatilisation of trifluralin, atrazine, metolachlor, chlorpyrifos and endosulfan from freshly tilled soil. J. Agric. Food Chem., 50, 4009 – 4017 10. Taylor, A. W. (1995) The volatilization of pesticide residues. In Environmental behaviour of Agrochemicals; Roberts, T. R., Kearney, P. C. Eds.; Wiley: London, U.K., pp 257 - 306 11. Thomson, W.T. (1982) Insecticides, Acaricides, and Ovicides Agricultural Chemicals, Book I. Thomson Publications, Fresno, CA. 12. Tomlin, C. (1994) The Pesticide Manual, 10th edition, The British Crop Protection Council, Surrey, UK and The Royal Society of Chemistry, Cambridge, UK 13. Vig, K., Singh, D.K., Agarwal, H.C., Dhawan, A.K. & Dureja, P. (2001) Insecticide residue in cotton crop soil. J. Environ. Sci. Health, B36(4), 421434 14. Wauchope, R.D., Buttler, T.M., Hornsby, A.G., Audustijn-Beckers, P.W.M. and Burt, J.P. (1992) The SCS/ARS/CES pesticide properties database for environmental decision making. Rev. Environ. Contam. Toxicol. 137: 1-157 15. Worthing, C.R. and Hance, R.J. (1991) 9th edition, The Pesticide Manual, The British Crop Protection Council, Unwin Brothers Limited, Surrey 16. Yen, J.H., Lin, K.H. and Wang, Y.S. (2000) Potential of the insecticides acephate and methamidophos to contaminate groundwater. Ecotox. Environ. Safety, 45, 79-86

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COMPARATIVE IMPLTMENTATION OF ra 9003 OF THE TWO BARANGAYS IN DANAO CITY, PHILIPPINES Maribel R. Blones National Irrigation Administration, Regional Office Xl, Bolton St., Davao City 8000, Philippines; Cell No. +639283379128; [email protected] ABSTRACT This study is all about the comparative implementation of Republic Act 9003 which is also known as the Ecological Solid Waste Management Act of 2000 of the two barangays in Davao City. A survey was conducted to obtain the data on the respondents’ socio economic profile, status of SWM implementation, barangay response, and the level of effectiveness in the implementation of RA 9003. The results showed that the implementation of Solid Waste Management Program of the two barangays differs on the approach of management. Governance and leadership of a leader has a relation with the citizen’s response in compliance to the application of the mandate of RA 9003. As a result, the two barangays were assessed to be ineffective in the implementation of RA 9003. The researcher recommended that their strengths and weaknesses shall be their benchmark for improvement. Key words: Solid Waste Management implementation INTRODUCTION The problem on solid waste and its management has become a challenging concern for the national government. The study made by the National Solid Waste Management Commission (NSWMC) estimated that in 2001, Philippines is generating over 38,249.37 tons of waste per day. Further, NSWMC in 2005 revealed every person living in the metropolis generates 0.5kg of waste daily. Metro Manila with an estimated population of about 10.5 million generates about 5,250 metric tons of waste per day, or 162,750 metric tons/month, equivalent to 1.95 millions metric tons/year. Hence, a study was conducted to ascertain the effectiveness of the implementation of RA 9003 by assessing the status of SWM implementation and the barangay response of the aforementioned barangays in compliance to the implementing rules and regulations of the Act. Research Problem. The purpose of the study is to describe the management and implementation of Republic Act 9003 in two selected barangays of Davao City. This study would like to identify the factors relevant to the realization of Solid Waste Management Program in Barangay Crossing Matina 74-A, Talomo District and Barangay 3-A, Poblacion District. Furthermore, the study would like to evaluate respondent’s responsiveness in as far as solid waste management is concern. Specifically, this study answers the following questions: 1. What is the socio-economic profile of the residents of the two selected barangays in Davao City in terms of:

36

a. income; b. educational attainment; c. tribe; d. household size; e. age; and f. civil status? 2. What is the profile of the commercial establishments in the two chosen barangays in Davao City in terms of: a. nature of business; b. type of business; and c. nature of waste? 3. What is the status of Solid Waste Management Program implementation in the two barangays in terms of: a. organization structure; b. plans and programs; c. leadership; and d. ordinances? 4. How did the two barangays respond to the Ecological Solid Waste Management Act 2000 known as Republic Act 9003 in terms of: a. planning; b. coordination; c. decision - making; d. implementation; and e. evaluation 5. What is the level of effectiveness in the implementation of Republic Act 9003 in terms of: a. education; b. engineering; c. enforcement; and d. economics and sustainability? Significance of the Study. The researcher would like to depict the strength and weaknesses in relation to the realization of Solid Waste Management Program within the barangay level. Republic Act 9003, if implemented successfully, will alleviate the waste crisis and build a framework for longer-term solutions. National Government. The findings will be able to help the national government enhance their strength and weaknesses in the implementation of solid waste management program as to organizational structure, technology, governance and leadership to attain the objectives of this Act. Local Government. This study will be able to assist the local government evaluate and refine their intensity and frailties in the realization of the Act as to manpower, budget, plans and programs, methodology and machineries, governance and leadership in their respective jurisdictions such as provincial, municipal or city government. Barangay. This study will be able to guide the barangay government in determining and improving their strength and weaknesses in the implementation of RA 9003 as to organizational structure, budget, plans and programs, technology, governance and leadership in their locality. City ENRO. This study will be able to help the City Environment and Natural Resources Office (City ENRO) enhance their strength and weaknesses in the implementation of Ecological Solid Waste Management Act as to organizational structure in accordance to manpower and budget, technology, governance and leadership in the enforcement of

37

the provisions of the Act. The Academe. This research can be used as reference in the study of governance practices and leadership behavior in the implementation of Republic Act 9003 known as Ecological Solid Waste Management Act 2000. Researcher. Being a concerned citizen the proponent would like to impart her studies on governance and leadership on the implementation of RA 9003 to the best of her ability and capacity to be able to contribute the acquired knowledge to the national, local and sub local government, City ENRO, and the academe. Research Design. This study used the descriptive survey research design. A survey questionnaire was employed to gather the qualitative data on the respondents’ profile; the barangay’s status of implementation in accordance to organization, plans and programs, leadership and ordinance; and the barangay’s response in terms of coordination, decision-making, implementation, and evaluation on the enforcement of RA 9003. To validate the implementation of RA 9003 of the two selected barangays, an evaluative instrument from Environmental Management Bureau was used. SWM experts from of the City Environment and Natural Resources Office, Department of Environment and Natural Resources, Environmental Management Bureau and School of Government and Management-University of Southeastern Philippines conducted the assessment on Solid Waste Management Programs of the aforementioned barangays in accordance to education, engineering, enforcement and economics and sustainability. The study is limited to the respondents’ profile, barangay’s organization, plans and programs, leadership and ordinances as well as, the methodology they have adapted. This includes the barangay’s response in accordance to planning, coordination, decision-making, implementation and evaluation. Solid waste generated in respondent residents and commercial establishments are the only focus of the study. Respondents. The respondents of the study are the barangay leaders, residents and commercial establishments of Barangay Matina Crossing 4-A and Barangay 3-A in Davao City, Philippines. Research Instruments. This study used survey questionnaire and evaluative instrument to gather data. Statistical Treatment. Percentage distribution was used to compute the descriptive difference of the two barangays in the respondents’ profile, the status of SWMP implementation and barangay response in the realization of RA 9003. Mean was employed to determine the level of effectiveness in compliance to the Implementing Rules and Regulations of Republic Act 9003. RESULTS AND DISCUSSION Respondents Socio economic Profile. From the National Statistical Coordination Board Food and Poverty Threshold for CY 2005-2007, the average monthly poverty threshold for a family of in the Philippines is PhP6, 195.00. Based on the statistical record, survey results shows that 55.2 percent of the total respondents of Barangay Matina Crossing 74-A has low income; while, 34.5 percent of the total respondents of Barangay 3-A have greater income than the baseline. The respondents of both barangays are educated. They both consist of various migrants. Most of the families have 5-7 members. With regards to age, 28.2 percent of the total respondents of Barangay Matina Crossing are of ages 21-30; and 31 percent of the total respondents in Barangay 3-A belong to ages 41-50. Majority of the residents are married.

38

Commercial Establishments. Most of the businesses of both barangays are engaged in the wholesale or retail such as eateries, sari-sari stores, bakeshops, etc. They have most likely the same business activities which is owned and operated by single proprietor. Though these commercial establishments practice disposal of segregated extras as to biodegradable and non-biodegradable solid wastes, there are still those who disposes mixed rubbish. Status of Implementation of Solid Waste Management Program.

Organization

Barangay Matina Crossing 74-A Successfully organized.

Plans and Have SWM plan of activities Programs Leadership Applied strategies coupled with ingenuity in governance and management with the participation of the community, barangay officials and other support groups. Indicator: SWMP developments can be observed.

Ordinances

 



 

Resolution No. 058-03 series of 2003 – creation of BSWMC Resolution for launching a special project on Waste Management under the Office of the Barangay ChairmanPurok Empowerment Development (OBC-PEDP) in coordination with the SB Committee on Health and Sanitation Program Resolution implementing RA 9003, an act providing SWMP, creating the necessary institutional mechanism and incentives, declaring certain acts prohibited and providing penalties, appropriating funds, and other purposes Resolution No. 080-03 series of 2003 – adoption of Ecological Solid Waste Management Program Resolution No. 19 series of 2003 – adoption and implementation of RA 9003 Section 48, penalizing among others the act of littering, throwing, pumping of waste in public areas, such as roads, sidewalks, canals, esteros or parks and establishments, or causing or permitting the same; open burning 39

Barangay 3-A Successfully organized. Inadequate SWM plan Lacks drive in governance and management to carrying out the mandate of the Act. Indicator: slow progress in the implementation of SWMP. Ordinance creating the Barangay Ecological Solid Waste Management Committee (BSWMC).

   

of solid waste, causing or permitting the collection of non segregated or unsorted waste. Ordinance No. 3 series of 2004 – implementation of SWMP Ordinance 2 series of 2004 – establishing the Material Recovery Facility (MRF) Resolution No. 079-03 series of 2003 – realignment of fund for the establishment of MRF. Resolution No. 17-04 series of 2004 – authorizing the Brgy Chairman to enter into contract with the landowner in the establishment of MRF.

Barangay Response to Republic Act 9003.

Planning

Coordination

Decision making

Barangay Matina Crossing 74-A Participatory approach was used which was participated by the respondents together with barangay leaders, and other support groups. The presence of SWM plan of activities motivated them to attentively respond to SWMP. This implies a satisfactory response. The players of SWMP implementation coordinated with each other. For consistency, the barangay also coordinated with the City ENRO in enforcing the programs of SWM. The presence of SWM plan of activities helped them comply the mandate of the Act. This reveals a very satisfactory response. Joint participation of the respondents and other support groups’ barangay is applied. This indicates a satisfactory response. 40

Barangay 3-A Participatory approach was employed which was participated by barangay officials, respondents and other support groups in the creation of BSWMC. They cannot move on due to inadequacy of SWM plan. This shows a poor and still improving response. Due to lack of SWM plan, the progress on the implementation of SWMP is slow. This implies a fair response.

Decision making is not yet realized which implies a fair response.

Implementation

Evaluation

Compliance was participated by the respondents and other support groups. This implies a satisfactory response. Substantially complied. This indicates a satisfactory response.

Slow development in complying the SWMP which indicates a fair response.

Evaluation is not yet realized which indicates a fair response.

Level of Effectiveness in the Implementation of RA 9003

Education

Engineering

Barangay Matina Crossing 74-A Training. SWM training and orientation was conducted which was participated by the respondents, ESWM personnel, and other support groups. Mobility. They have a functioning barangay SWM trainers group which takes charge of disseminating the concept and techniques of recycling to the household level. They have organized a functioning BSWMC. Campaign. Leaflets were distributed to the residents of the community. They have video showing the ESWM program to visitors or local residents. They have radio and TV program during the period of awareness drive. Segregation of household waste at source is being practiced by some respondents. No system of treating compostable waste. No system to control odor and insects at collection area. Established a Material

41

Barangay 3-A Training. SWM training and orientation was conducted which was participated by the barangay officials, and barangay staff. Mobility. Other groups like NGO’s, PO’s, and other volunteers exist. They have organized a functioning BSWMC. No campaign materials used.

Due to lack of awareness disposal of mixed rubbish is still being practiced by the respondents. They have not established a Material Recovery Facility.

Enforcement

Economics and Sustainability

Recovery Facility. No trained personnel to operate the recycling operation. They have SWM plan of activity. They give incentives or awards to entities that practice ESWM within the barangay. They have created a resolution for violators of RA 9003. The barangay is inefficient in the maintenance of drainage systems and waterways, and in the maintenance of sidewalks and roads from litter. At source, the respondents sell their stored recyclable and reusable solid waste to ambulant buyers of junks. At the MRF, the collected and stored recyclable and reusable wastes are sold to junkshops. The back of MRF structure was utilized as vegetable garden. They sell the products and the proceeds are income of the barangay.

Inadequate SWM plan. They do not have the motivating drive. They have not created a resolution for violators of RA 9003.

Household practice to sell their stored recyclable and reusable solid wastes directly to ambulant buyers of junks.

As per evaluation using the Environmental Management Bureau (EMB) evaluative instrument, both barangays did not reach the passing merit points of 600. Barangay Matina Crossing 74-A has attained a merit of 311 while Barangay 3-A has a merit of 32.33. CONCLUSIONS

The following conclusions are drawn from the above findings: The respondents of Barangay Matina Crossing 74-A are of low income; educated; consisted of various migrants mostly Bisaya; composed of 5-7 members per family; many are in ages 21-30; majority are married. Whereas, the respondents of Barangay 3-A are of higher income; educated; consisted of various migrants mostly Bisaya; composed of 5-7 members per family; many are in ages 41-50; majority are married.

42

The commercial establishments in both barangays are mostly engaged in wholesale or retail. Most of the businesses are managed and operated by single proprietor. They both dispose mixed trash. Barangay Matina Crossing 74-A has a better status of implementation of SWMP under RA 9003 than Barangay 3-A in terms of organization, plans and programs, leadership, and ordinances passed. Barangay Matina Crossing 74-A has a better barangay response to RA 9003 than Barangay 3-A in terms of planning, coordination, decision making, implementation, and evaluation. Both barangays were assessed to be ineffective in the implementation of RA 9003. They have not reached the passing merit points as per EMB evaluative instrument. ACKNOWLEDGEMENTS The researcher of this study is thankful to the following persons for their support and assistance: Hon. Joel Santes, Barangay Captain and BSWMC Chairman of Barangay Matina Crossing 74-A; Hon. Pedro Tombo, Barangay Captain and BSWMC Chairman of Barangay 3-A, Rusela Y. Pepito, Carmelita P. Martinez, Ariesteo C. Salapa, Rita Fe C. Sison, Hernan Roxas, Albert B. Jubilo, and Nestor Amable. REFERENCES Madrazo, E.P. (2003). Primer on Household Solid Waste Management. Davao City, Philippines, CENRO Tjosvold, D. & Tjosvold, M. (1995). Psychology for Leaders: Using Motivation, Conflict, and Power to Manage More Effectively. New York: wiley Solid Waste Management Operation Profile of Davao City. CENRO, 2001-2002. Status of LGU-Wide Ecological Waste Management System. Davao City, Philippines, CENRO, November 30, 2004. Implementing Rule and Regulations of Republic Act 9003, Administrative Order No. 2001-34. Manila, Philippines, 2001. Elements of Good Governance. Retrieved http://www.adb.org/Governance/gov_elements.asp.

January

19,

2005.

From

Guiding Principles of Solid Waste Management: An Information Brochure on Republic Act 9003 The Ecological Solid Waste Management Act of 2000. Manila, Philippines. DENR, 2000.

43

DDT RESIDUE IN SOIL AND WATER IN AND AROUND ABANDONED DDT MANUFACTURING FACTORY M. Rasul Jan1, Jasmin Shah, Kashif Gul and Mahmood A. Khawaja2 1

Institute of Chemical Sciences, University of Peshawar, N.W.F.P., Pakistan E-Mail:[email protected] 2 Sustainable Development Policy Institute (SDPI), Islamabad, Pakistan Fax:92-91-9216652, e-mail:[email protected]

ABSTRACT DDT (Dichlorodiphenyltrichloroethane) belongs to one of the most hazardous groups of chemicals called Persistent Organic Pollutants (POPs), also known as “The Dirty Dozen”. These very toxic chemicals, including DDT are long lasting due to their nondegradability, can travel to distant places and being fat soluble can accumulate in animals and human bodies. Due to the persistent nature of DDT, its adverse environmental and health impacts, the present study was undertaken to examine the residual DDT in and around abandoned DDT manufacturing factory in Amman Gharh, Nowshera, NWFP. Samples of soil, sediments and water were collected in and around the factory area, nearby DDT stores, main factory drain leading to river Kabul and nearby villages. Standard procedures were used for the collection, transportation and storage of samples for analyses. Extraction of each sample for DDT analyses was carried out in triplicates using Soxhelt extraction apparatus. The extract was transferred to clean, dry glass vial, sealed and put in the refrigerator. DDT contents in the samples were determined by GC using capillary column and electron capture detector. Identification was done on the basis of their retention time and spiking with standard and quantified on the basis of peaks areas. Most of the samples collected up to half kilometer distance from the site of the DDT factory were found contaminated. Further the level of DDT decreased with increasing depth from top to bottom and with distance from the site. The results indicate that there is no immediate threat to underground water reservoirs. Keywords: POPs, DDT, contamination, soil, water. INTRODUCTION A huge variety of pesticides of varied chemical forms are currently in use for agricultural purpose all over the world and are detected in various environmental matrices like soil, water and air. The toxicity of these chemical species depends on their chemical forms. Organochlorines are known to resist biodegradation and therefore they can be concentrated through food chain. As a result this group of organic compound constitutes one of the most dangerous groups of organic contaminants and is also known as persistent organic pollutants (POPs) or the dirty dozen. Due to its long lasting nature these toxic chemicals including DDT can travel to distant places and being fat soluble it accumulate in animals and human bodies. The environmental contamination by POPs residue has been widely documented in several countries (Blasco et al., 2004; Cruz etal., 2003; Dascenzo et al., 1998). To save public health especially the health of children, the manufacturing and use of 44

POPs have been banned in the world under Stockholm convention on POPs, in-acted in 2001. A number of national governments including Pakistan have signed the Stockholm convention and so for also ratified by over 120 countries. Pesticides determination particularly POPs in food and agricultural products are necessary to guarantee consumer health (Driss et al., 1994). Chromatographic methods particularly gas chromatography (GC) and liquid chromatography (LC) are preferred for pesticides determination. Since almost all pesticides contain heteroatoms, the most commonly used element-selective detectors for GC are nitrogen-phosphorus (NPD), flame photometric (FPD) and electron-capture detectors (ECD). Regardless of the selectivity of the detector GC–MS provide useful structural information (Grimalt et al., 2004). The extraction procedures used are solid phase extraction using different material modification (Hong-Ping et al; 2003; Hussain et al., 2001; 2002; Jan and Cerne 1993; Jimenez et al., 1998). Incase of water samples liquid liquid extraction using immiscible solvent followed by cleanup procedure and GC determination is also used (Jimenez et al., 1998; Krauss and Wilcke, 2005). A variety of methods have been used for the determination of pesticide residues in soil and water (Lino et al., 1998; 1999; Marzycka, 2002; Parrila and Vidal, 1997; Quayle, 1997; Tomkins and Sega, 2001). In the present work, a gas chromatograph with a capillary column and electron capture detector were employed for DDT residue analysis in soil and water samples collected from in and around abandoned DDT factory site Nowshera. EXPERIMENTAL Apparatus GC-14A gas chromatograph (Shimadzu Instruments, Tokyo, Japan) equipped with a capillary column and Ni63 electron capture detector was used. Chromatographic separations were performed using a fused-silica capillary column (25 mm × 0.53 i.d.) with a film thickness of 0.15 µm. Nitrogen served as the carrier gas at a flow rate of 3.0 mL/min in constant flow mode. The temperature of the injector was 240 °C, and that of the electron capture detector was 280 °C. The oven temperature was programmed as follows: 80 °C for 2.0 min, increasing to 160 °C at 20 °C/min and holding for 1.0 min, increasing to 250 °C at 4 °C/min and holding for 5.0 min, and finally increasing to 275 °C at 10 °C/min and holding for 5.0 min. Reagents Authentic DDT standards were purchased commercially. Other chemicals and solvents used were of analytical-grade purity. Sampling In the first phase soil samples from within the DDT factory area, its surroundings, in and around Nowshera were collected. Water samples were collected from tube well in the locality close to the site of demolished DDT factory. Water samples were also collected from the drainage leading to Kabul River and from Kabul River. In the second phase eighty one soils samples were collected with in half kilometer distance from the gate of the factory in eight directions that is North (N), North West (NW), West (W), South West (SW), South (S) South East (SE), East (E) and North East (NE) and at different depths ranging 0 to 18 inch.

45

Samples preparation Soil samples All the stones, pebbles and organic matter etc were removed from the sample collected. It was dried in oven at 60°C for overnight, well mixed and sieved. It was ground and brought to uniform size and stored for further use. Procedure for Extraction of DDT from Soil Sample Extraction of each sample was carried out in triplicates using standard procedure (Tsipi et al., 1999; Valor et al., 2001). In brief 50g of each soil sample was taken in a thimble and placed in soxhelt extraction apparatus. The apparatus was placed on the water bath and the temperature of the water bath was kept below 100°C. The sample was then extracted with 150 ml of methanol in a soxhelt extraction apparatus for 4 hours. The volume of the sample was reduced to 20 ml in the same apparatus. 0.25 ml were taken from the original sample and diluted up to 10 ml with methanol. It was transferred to well washed, clean, dry glass vial sealed and put in the refrigerator till analysis. Extraction from Water Sample Liquid-liquid extraction procedure was adopted for extraction of pesticides from water samples. 25 ml of each water sample was taken in conical flask and 10% NaCl (sodium chloride) was added to it, followed by addition of 125 ml ethyl acetate. It was then stirred for 15 minutes. The contents of the volumetric flask were transferred to separatory funnel for separation of the two phases. The organic phase was separated and evaporated on Rotary evaporator at 45 °C under vacuum and optimum rotation speed until the complete dryness of the sample. After the complete dryness the contents were reconstituted in 5 ml n-Hexane for analysis on GC (Vinas et al., 2002). RESULTS AND DISCUSSION The results of DDT contents in soil and water collected in the first phase is given in table 1&2 and shown as a bar graph in figures 1& 2 respectively. It was observed that most of soil samples analyzed had very low level of DDT contents. Water samples also showed traces of DDT despite the fact that the factory had stopped operation in 1994. Soil samples (S.No.1, 3-5) from within factory formulation unit showed residual DDT in the range 242.28 ± 0.81 to 573.03 ± 0.94 ug/g. DDT levels in the soil samples (S.No.6-8) at different points outside the factory compound were found to be in the range 558.36 ± 0.71 to 780.41 ± 0.54 ug/g. In the drain samples (S.No.12-15) DDT levels were found in the range 388.58 ± 0.48 to 1631.70 ± 0.61 ug/g. Highest DDT levels of 2822.080 ± 0.88 ug/g and 2841.45 ± 0.95 ug/g were found in samples (S.No.2 & 10) from the left-over old bags in the formulation unit and in the stores. Soil samples (S.No.11) taken from five yards outside the stores showed 1858.03 ± 0.78 ug/g residual DDT. However, DDT was not detected in the soil sample (S.No.16) taken from Azakhel (control) ten kilometer away from DDT factory. Residual DDT levels in water samples from within the vicinity of DDT factory, nearby villages and drain leading to river Kabul showed little variation, most of the samples falling in the range 0.20 ± 0.23 to 0.31 ± 0.03 ug/ml (Table 2). Highest and lowest DDT levels were found to be 0.40 ± 0.14 (S.No.2) and 0.07 ± 0.10 ug/ml (S.No.6), respectively. It appears that 46

either the DDT in the sediments along the factory drain and surrounding soil has already been eroded away or erosion process is too little and very slow. No relationship was observed between DDT levels in the samples studied and the distance of the sampling points from the DDT factory. Soil samples collected at various depth levels at various locations and at different distances in each direction from the abandoned DDT factory were analyzed and the results are given in the tables 3 and 4. Similarly these values are shown in bar graphs in all directions, at different distances and at various depths from surface soil to 0-6, 6-12, 12-18 inch in figure 3-9 respectively. As can be seen from these tables and graphs that traces of DDT are present in most of the samples analyzed. The presence of DDT residues in soil samples collected from the vicinity of DDT factory shows that the soil is contaminated. The soil samples collected from the front of DDT factory, an area that is mostly residential area is highly contaminated like North West, West, South West, South, South East and East sides. The value of DDT residue varies from 0.01-11.3µg/g, 8.29-10.46µg/g, 5.519.96µg/g, 2.94-9.59µg/g, 5.19-8.55µg/g, 4.14-8.27µg/g in these sites respectively. The samples from North and North East sides of the abandoned site show that the value of DDT in these samples varies from 0.01-0.02µg/g, 0.01-0.04µg/g respectively. Table 4 shows the DDT level in soil at various depths ranging from 024 inches. It was observed in all soil samples that there was decrease in the level of DDT as one go from top to bottom indicating that there is not much leaching. This could be attributed to the nature of the soil with high organic matter. In most of the soil the concentration of DDT drops to below detection level when we reach to the depth of 18 inches. Further the results shows that the samples collected within the site of the factory are most contaminated. As the distance from the factory increases, the level of DDT decreases. This decrease is more pronounced towards South East direction. It is evident from the analytical data presented in tables 1-4 and shown in figures 3 to 9 that both water and soil are still contaminated with DDT, despite the closure of the DDT factory over the past so many years. These results indicate that DDT contamination in and around DDT factory in Amman Gharh areas may cause most serious consequences for ecosystem function, food safety and other aspects of human health of the surrounding locality. CONCLUSION The results of the soil and water samples collected in the first phase indicated the presence of DDT in the demolished site of the abandoned DDT factory necessitating further study. The results of the soils samples collected in the second phase indicated that almost up to half a kilometer in all direction from the abandoned sites, the soil was found contaminated. The results of the soil analyses at various depths indicate that leaching is very slow and there is no immediate threat to underground water sources. It may be concluded that to safeguard the health of the surrounding locality the site may declared hazardous and banned for all kind of activities until remedial measure are taken.

47

REFERENCES: 1. Blasco, C., Lino, C.M., Pico, Y., Pena, A., Font, G., Silviera, M.I., 2004. Determination of organochlorine pesticides residues in honey from the central zone of Portugal and Valencian community J. Chromatogr. A, 1049 (1-2) 155-160. 2. Cruz, S., Lino, C., Silviera, M.I., 2003. Evaluation of organochlorine pesticides residues in human serum from an urban and two rural populations in Portugal. Sci.Total Environmental 317(1-3) 23-35. 3. Dascenzo, G., Gentili, A., Marchese, S., Perret, D., 1998. Determination of arylphenoxypropionic herbicides in water by liquid chromatography– electrospray mass spectrometry. J Chromatogr A 813 (2): 285-297. 4. Driss, M.R., Zafzouf, M., Sabbah, S., Bouguerra, M.L., 1994. Simplified procedure for organochlorine pesticides residue analysis in honey. Int. J. Eviron. Anal. Chem. 57(1), 63-71. 5. Grimalt, J.O., Van Drooge, B.L., Ribes,A., Vilanova, R.M., Fernandez, P., Appleby, P., 2004. Persistent organochlorine compounds in soils and sediments of European high altitude mountain lakes. Chemosphere 54(10), 1549-1561. 6. Hong-Ping Li, Gwo-Chen L.J., 2003. Determination of organochlorine pesticides in water using microwave assisted headspace solid-phase microextraction and gas chromatography. J. of Chromatogr. A, 1012 (2), 129137. 7. Hussain, A., Asi, M. R., Iqbal, Z., 2001. Dissipation and degradation of 14CDDT in Tando Jam (Sindh) soil under field conditions. Pak j. anal. Chem 2, 14-18. 8. Hussain, A., Iqbal, Z., Asi, M. R., Mohammad, A., khan, T. A., Dissipation and degradation of 14C-DDT in Potohar area Islamabad soil under field conditions. 2002. Pak j. anal. Chem., 3(1, 2) 48-51. 9. Jan, J., Černe, K., 1993. Distribution of some organochlorine compounds (PCB, CBz, and DDE) in beeswax and honey. Bull. Environ. Contam. Toxicol. 51(5), 640-646. 10. Jiménez, J.J., Bernal, J.L., del Lozal, M.J., Martín, M.T., Mayorga, A.L., 1998. solid phase microextraction applied to the analysis of pesticide residues in honey using Gas Chromatography with electron capture detection. J. Chromatgr. A 829 (1-2), 269-277. 11. Jiménez, J.J., Bernal, J.L., del Lozal, M.J., Toribio, L., Martín, M.T., 1998. Gas Chromatography with electron capture and nitrogen-phosphorus detection in the analysis of pesticides in honey after elution from a florisil column influence of the honey matrix on the quantitative results. J. Chromatogr. A 823 (1-2), 381-387. 12. Krauss, M., Wilcke, W., 2005. Persistent organic pollutants in soil density fractions: distribution and sorption strength Chemosphere 59(10), 1507-1515. 13. Lino, C.M., Azzolini, C.B.F., Nunes, D.S.V., Silva, J.M.R. da Silveira, M.I.N., 1998. Methods for determination of organochlorine pesticide residues in human serum. J. Chromatogr. B 716 (1-2), 147-152. 14. Lino, C.M., Guarda, L.M.C., Silviera, M.I.N., 1999. Determination of organochlorine pesticides residues in medicinal plants sold in Coimbra, Portugal JAOAC Int., 82(5)1206-1213.

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15. Marzycka, B., 2002. Simple method for the determination of trace levels of pesticides in honeybees using matrix solid-phase dispersion and gas chromatography. J. Chromatgr. A 982 (2). 267-273. 16. Parrilla, P., Vidal, JLM., 1997. Determination of Pesticide Residues in Water Using LLE or SPE and HPLC/DAD Detection Anal Lett 30 (9): 1719-1738. 17. Pico, Y., Viana, E., Font, G., Manes, J., 1995. Determination of organochlorine pesticides content in human milk and infant formulas using solid phase extraction and capillary Gas Chromatography. J.Agric.Food Chem.43, 1610-1615. 18. Quayle, WC., Jepson, I., Fowlis. LA., 1997 Simultaneous quantitation of sixteen organochlorine pesticides in drinking waters using automated solidphase extraction, high-volume injection, high-resolution gas chromatography. J Chromatogr A 773 (1-2): 271-276. 19. Tomkins, BA., Sega, GA., 2001. Determination of thiodiglycol in groundwater using solid-phase extraction followed by gas chromatography with mass spectrometric detection in the selected-ion mode. J Chromatogr A 911 (1): 8596. 20. Tsipi, D.,Triantafyllou, M., Hiskia, A., 1999. Determination of organochlorine pesticides residues in honey applying solid phase extraction with RP-C18 material. Analyst 124, 473-475. 21. Valor, I., Perez, M., Cortada, C., Atraiz, D., Maltoand, JC. Font. G., 2001. SPME of 52 pesticides and polychlorinated biphenyls: Extraction efficiencies of the SPME coatings poly(dimethylsiloxane), polyacrylate, poly(dimethylsiloxane)-divinylbenzene, Carboxen-poly(dimethylsiloxane), and Carbowax-divinylbenzene. J Sep Sci 24 (1): 39-48. 22. Vinas, P., Campillo, N., Lopez-Garcia, I., Aguinagia, N., Hernandez-Cordoba, M., 2002. Determination of pesticides in waters by capillary gas chromatography with atomic emission detection J. Chromatogr. A, 948 (1-2) 249-256.

49

Table 1: DDT Residue in Soil Samples (µg/g) S .NO 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.

Sample Name

Mean conc. (µg/g)

Sample taken from the inner side of the wall of 242.29± 0.81 formulation unit. Sample taken from Bags which were present their in 2822.08± 0.88 the formulation unit Sample taken from within the factory (formulation 399.22± 0.9 unit) Sample taken from within the factory (formulation 573.03±0.94 unit) Sample taken from within the factory (formulation 327.59±0.63 unit) Sample taken from outside the factory at depth 3 780.41±0.54 inch Sample taken from outside the factory at depth 3 599.21±0.98 inch Sample taken from end of the drainage near the 558.36±0.71 factory wall Sample taken from material from left over bags from 7.50± 0.11 store house1 and 2 Sample taken from material from left over bags from 2841.45±0.95 Store house1 and 2 Sample taken from 5 yards near old store house 1858.03±0.78 D4 start of the drain towards Kabul river depth 7 1631.70±0.61 inches D3 ends of the drain towards Kabul River 629.05±0.18 D2 ends of the drain towards Kabul River 388.58± 0.48 D1 ends of the drain towards Kabul River 1039.35±0.75 Control soil sample taken from Azakhel near petrol ND pump

ND: Not Detected.

50

Table 2: Concentration of DDT in water μg/mL S.NO

Sample Name

1.

Sample taken from the mosque near the DDT factory

2.

Sample taken from petrol pump on the G.T Road side in Amangarh Sample taken from the tape of the mosque of Gharib Abad area This sample taken at the end of drain 10Yards away from bank of Kabul River This sample taken at the end of drain 10Yards away from bank of Kabul River KRDW3 (Kabul river drainage water 3) KRDW4 (Kabul river drainage water 4) Well water 1 Well water 3

3. 4. 5. 6.

7. 8. 9.

51

Mean conc. (µg/mL) 0.22± 0.01 0.40± 0.14 0.31± 0.11 0.31± 0.03 0.20± 0.23 0.07± 0.10

0.22± 0.02 0.21± 0.04 0.30 ± 0.21

Concentration (ug/g)

Figure 1: Concentration of DDT in soil samples (µg/g) 3000 2500 2000 1500 1000 500 0 1 2 3 4

5 6 7 8 9 10 11 12 13 14 15 16 Sample Number

concentration(ug/g)

Figure 2: Concentration of DDT in water samples (µg/ml) 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 1

2

3

4

5

6

Sample Number

52

7

8

9

Table 3: DDT Residue in Soil Sample (µg/g) S.No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

Sample A1 A2 A3 A4 AD1 AD2 AD3 AD4 AD5 AD6 AD7 AD8 B1 B2 B3 B3.1 B3.2 B3.3 B3.4 B3.5 D1 D2 BD1 BD2 BD3 BD4

pH Conc. (ug/g) 4.8 0.02 4.3 0.02 4.9 0.01 4.6 0.01 4.8 11.3 4.9 8.96 5.1 3.06 4.8 0.01 4.7 0.01 4.7 0.04 4.7 0.03 4.6 0.01 4.8 9.59 4.7 7.99 4.7 5.08 4.9 4.61 4.8 2.70 4.7 3.35 4.6 2.26 4.6 2.94 4.9 10.46 4.7 8.29 5.0 9.96 4.8 8.89 4.6 7.70 4.8 7.58

S.No. 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51

Sample BD5 BD6 BD6.1 BD6.2 AC1 AC2 AC3 AC4 AC5 AC6 AC7 AC8 C1 C2 C3 C4 C5 C6 BC2 BC3 BC4 BC5 BC6 BC7 BC8

pH 4.8 4.7 4.9 4.8 4.5 4.6 4.6 4.5 4.5 4.8 4.8 4.9 4.8 4.6 4.7 4.5 5.0 5.0 5.0 4.9 5.0 4.9 4.9 4.8 4.9

Conc. (ug/g) 6.53 6.14 4.95 5.51 0.01 0.01 0.03 0.04 0.02 0.01 0.01 0.01 8.27 7.82 5.69 6.24 3.87 4.14 8.55 7.86 5.75 7.43 6.28 5.86 5.19

Distance (in yards) from gate of DDT Factory: 1 = 70; 2 = 140 yards; 3 = 210; 4 = 280; 5 = 350; 6 = 420; 7 = 490; 8 = 560 Samples points directions from the DDT Factory gate: ADD = North West; D = West; BDD = South West; B = South; BCD = South East; C = East

53

Table 4: Concentration of DDT in Collected soil sample at various depths. Sample code ADD0 ADD1 ADD2 ADD3 ADD4 DD0 DD1 DD2 DD3 DD4 BDD0 BDD1 BDD2 BDD3 BDD4 BCD0 BCD1 BCD2 BCD3 BCD4 BB0 BB1 BB2 BB3 BB4 CC0 CC1 CC2 CC3 CC4

Conc.(µg/g) 9.95 8.18 7.03 3.74 0.01 10.62 6.30 3.91 3.02 0.58 1.73 1.77 0.05 0 0 2.14 2.14 0.85 0 0 8.31 4.50 1.28 0 0 4.94 3.90 0.02 0 0

Mean.

5.78±3.94

4.88±3.80

0.71±0.95

1.03±1.08

2.82±3.58

1.77±2.45

Soil Samples from depth (inches): 0 = 0; 1 = 6; 2 = 12; 3 = 18; 4 = 24 Samples points directions from the DDT Factory gate: ADD = North West; D = West; BDD = South West; B = South; BCD = South East; C = East

54

Average Conc.

Figure3: Results of DDT average concentration in different directions.

7 6 5 4 3 2 1 0

North West South South South East MRL West West East Direction

Figure 4: Bar graph of average concentration at different distance from DDT factory.

Conc. (ug/g)

10 8 6 4 2 0 65

130

195

260

325

390

Distance in meter

55

455

520

Average Conc.(ug/g)

Figure 5: DDT concentration in different direction for surface soil(0 inches depth).

12 10 8 6 4 2 0

or N

th

t es W

t t es es W hW ut o S

u So

th

st Ea

h ut o S Direction

st Ea

M

L R

Average Conc. (ug/g)

Figure 6: DDT concentration in different direction at 0- 6 inches depth. 9 8 7 6 5 4 3 2 1 0

or N

th

t es W

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Figure 7: DDT concentration in different direction at 6-12 inches depth.

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Figure 8: DDT concentration in different direction at 18 inches depth. 4 3.5 3 2.5 2 1.5 1 0.5 0

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Figure 9: DDT concentration in different direction at 12-24 inches. 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

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COMBINATION OF ADVANCED OXIDATION PROCESS (AOP) WITH MEMBRANE BIOREACTOR (MBR) SYSTEM FOR ZERO SLUDGE PRODUCTION Putri. N. Faizura, M. Roil Bilad, Hilmi Muktar Universiti Teknologi PETRONAS, Bandar Seri Iskandar (31750), Tronoh, Perak, Malaysia Email: [email protected] ABSTRACT In order to prevent excess sludge production during wastewater treatment, an advanced oxidation process-membrane bioreactor (AOP-MBR) system has been introduced. In this system, a part of sludge is recycled from MBR to the AOP. The objective of this study is to develop simple mathematical model for AOP-MBR system. The operational parameters were exploited to describe the performance of the process. The simulation on degradation of substrate in the system reactor showed the effectiveness of AOP reactor to complement MBR in treating recalcitrant pollutant. Degradation of substrate (A), metabolite product (S), and biomass (X) in AOP reactor were described using the proposed model. It was found that, the depletion of sludge concentration in AOP reactor was key factor to attain zero excess sludge production. It was strongly affected by hydrolysis rate constant (kX), recycle ratio (r), concentration of sludge from MBR (CX2), and residence time of AOP reactor. The control of sludge concentration level could be conducted by manipulating the recycle ratio. Keywords: Membrane bioreactor (MBR); Advance oxidation process (AOP); Sludge reduction; Modeling INTRODUCTION The treatment of wastewater using activated sludge process produces a considerable amount of excess sludge that has to be wasted. The expense for excess sludge treatment for conventional activated sludge system has been estimated to be 50–60% of the total expense of wastewater treatment plant [Egemen, 2001]. Moreover, treatment of produced sludge tend to be more complicated compared to the activated sludge process itself. Applying conventional disposal method of excess sludge by land-filling causes a secondary pollution problem. Therefore the interest for development of new methods to reduce the volume and mass of the excess sludge has been rapidly growing. Recently, application of MBR in treatment of wastewater proves the ability to reduce excess sludge production. The sludge is completely rejected and remained in bioreactor. It significantly increases the sludge retention time (SRT) and sludge concentration inside bioreactor from 2-3 g·l-1 to 10-15 g·l-1. By increasing the sludge concentration, the production of sludge is reduced down to zero. This may occur under very low F/M ratio such as 0.07 kgCOD·kgMLSS-1·day-1 [Rosenberg, 2000] or 0.066 kgCOD·kgMLSS-1·day-1 [Yasui, 1996]. However, the high sludge concentration

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limits the membrane filtration performance, results the low flux operation, requires high cleaning intensity, reduces the membrane lifetime, and produces the extracellular polymeric substances (EPS) that lead the membrane fouling. The excess mechanical shear arise by high flow rate pump can also be used to reduce the excess sludge in cross flow type MBR [Yoon, 1999]. Ozonisation has been applied to reduce the excess sludge production. The sludge is taken from aeration basin or returned sludge from clarifier and disintegrated by ozone. The disintegrated sludge than returned to aeration basin again. For conventional activated sludge, Egemen et al. [2001] could reduce 40-60% of excess sludge. The complete excess sludge prevention was obtained by Yasui et al (1996), and Sakai et al (1997) under low organic loading of F/M=0.1 and F/V=0.49 kgCOD·m-3·day-1 in MBR system. Application of ultrasound-MBR system could successfully prevent excess sludge production in high organic loading of 1.01 kgCOD·m-3·day-1 [Yoon and Kim, 2001]. In this system, some amount of sludge was collected directly from the aeration tank of MBR and was disintegrated with soniciter and then supplied to the MBR as the feed solution. By this method, the steady-state MLSS in the aeration tank could be maintained to be 7.5 g·l-1. The application of MBR-sludge disintegration (MBR-SD) system has been proposed recently by Yoon (2003). In this system, the aeration basin of MBR is equipped with separated sludge disintegration unit. This sludge disintegration unit promotes the sludge decay by an artificial sludge disintegration process such as ultrasound, ozone, ball mill, alkaline treatment, microwave, etc. The objective of this study is to provide simple mathematical model which is able to estimate some operational parameter that can be applied in order to attain the zero sludge production in AOP-MBR system. THEORY The concept of zero sludge production in AOP-MBR system In conventional MBR system, new sludge is continuously generated with consumption of organic materials while some sludge is decayed by endogenous respiration. However, the rate of sludge decay is not equal with the rate of sludge production. As a result some excess sludge must be removed to maintain the sludge operational concentration. Therefore, in order to attain zero excess sludge production, sludge decay rate must be increased artificially. The proposed reactor system is shown in Figure 1. The system consists of membrane bioreactor (MBR) and advanced oxidation process (AOP). The AOP is used to pre oxidize poor-biodegradable substrate (A) as main pollutant and enhances cell decay rate in MBR by recycling certain amount of MBR liquor from aeration tank.

Figure 1 Preliminary schematic of AOP-MBR system for zero excess sludge production.

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Advanced oxidation process (Photo-chemical oxidation) The oxidation of A in AOP produces the intermediate component (S) that can also simultaneously be oxidized to produce H2O and CO2. In AOP reactor, recycled sludge is hydrolyzed to form intermediate (S). So in the AOP reactor, three reactions occur: A  a S + CO2 + H2O, rA=-kA CA

(1)

X  b S + CO2 + H2O, rX=-kX CX

(2)

S  CO2 + H2O, rS=-kS CX

(3)

where a and b are stoichiometric coefficients, generally less than one for this single intermediate, which represent the gram of S formed per gram of A or X photodegraded, kA, kX, and kS is the kinetic constants for photo-chemical oxidation of A, X, and S respectively. The AOP reactor is conducted in CSTR reactor. To simplify the mathematical model, a first order reaction with respect to concentration of contaminant is assumed. Considering the mass balance of contaminant A in AOP reactor: V1 dN A  FAi  FA 2  FA1   rA dt (4) dt 0 dN A At steady state, 0 (5) dt FAi  FA 2  FA1   rAV (6) Q1  Qi  Q2 (7) Q Q r  2 , so i  (1  r ) (8) Q1 Q1 Substitution of (r) and by integrating the biodegradation kinetic rate to get: (1  r )C Ai C A1  (9) 1  k A 1 where V is AOP reactor volume, dNA/dt is the rate of accumulation of A in reactor, r is defined as the ratio of feed to recycle flow rate, CAi is concentration of A in feed, CA1 is concentration of A inside the reactor, τ1 and equal to V1/Q1 that represent the residence time of AOP reactor. Using similar approach, by calculating the mass balance of sludge and intermediate S to get: rC X 2 CX1  1  k X1 (10)

C S1 

rC A 2   1 ak A C A1  bk X C X 1  1  k S 1

(11) where CSi is the concentration of S in AOP-MBR feed, CA2, is the concentration of recycled A, and CX1 is concentration of non oxidized sludge in AOP reactor.

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Membrane bioreactor (MBR) In MBR, biological degradation of chemical compounds by the microorganism is taken place. Usually it results in cell growth and gives energy for cell maintenance. To simplify the model, it is assumed that the intermediate compound S that is formed in AOP reactor is the only substrate for the bioreactor and that the compound A that leaving the AOP reactor is not biodegraded in MBR. In bio-kinetic point of view, S is easier to biodegrade than A. A common functional relationship between the specific growth rate of sludge µ (h-1) and the concentration of essential compound (substrate) is Monod equation:  C   max Sb  k d C sb K S  C Sb (12) where µmax is the cell maximum specific growth rate (h-1), KS is the value of the substrate concentration at which the specific growth rate is half of it maximum value (g·l-1), and CSb is the concentration of limiting substrate in bioreactor (g·l-1). Considering the mass balance of biomas (X) in MBR reactor at steady state: V

Q1C X 1  Q2 C X 2  Q3C X 3   rX dV  0 0

(13)

Q1C X 1 

 max C S 2 C X 2V2  k d C X 2  Q2 C X 2  Q3C X 3 K S  CS 2

(14) Where Q is the volumetric flow rate (l), kd is he rate constant of endogenous respiration, CS2 is the substrate S concentration in bioreactor, CX2 is sludge concentration in MBR, CX3 is sludge concentration at effluent. C By considering that X 1  0 and divide the above equation by Q and CX2 to get: CX 2

 max CS 2 1 k    r  d  K S  CS 2  2   2  (15)  1 k   max C S 2  K S  CS 2  r  d  2  2  (16)  k  K  k 1 C S 2   max   r  d   S  r  d  2   2   2   2  (17) If α is defined as: 1 k     r  d  2  2  (18)

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  

CS 2  CS3 

K S  max  

(19) Where τ2 is the residence time in MBR that equal to V2/Q3, By defining sludge yield (Y) as: Y=mass of cell formed/mass of substrate consumed, the mass balance of substrate S in MBR can be written as follow: V

Q1C S 1  Q2 C S 2  Q3C S 3   rS dV  0 0

(20)

Q1C S 1 

1  max C S 2 C X 2V2  Q2 C S 2  Q3C S 3 Y K S  CS 2

(21) By dividing by Q will get: 1  max C S 2 CS1  C X 2 2 2  rC S 2  (1  r )C S 3 Y K S  CS 2 (22) 1  max CS 2 CS1  C X 2 2  CS 2 Y K S  CS 2 (23) Y K S  CS 2 C S 1  C S 2  CX 2   2  max C S 2 (24) RESULTS AND DISCUSSION The variables that are used in the calculation are summarized in Table 1. The range of reported first-order particulate hydrolysis constant (kX) was broad i.e. 0.06-2.2 day-1. In addition, the maximum specific growth rate and half saturation constant also have broad range because they depend on the feed organic material constituent and biodegradability. The range of 0.16-3 h-1 for µmax and 0.022-0.355 g·l-1 for KS were considered in order to investigate the effect of µmax and KS on performance of AOPMBR system. Table 1 Values of kinetic and stoichiometric parameters used in calculation. Parameter kX kA kS µmax KS kd

Unit day-1 h-1 h-1 h-1 g·l-1 h-1

Value 0.06-2.2 1-10 0.05-1 0.16-3.0 0.022-0.355 0.0015-0.0667

Reference Yoon (2003) Espulgas et al (1993) Espulgas et al (1993) Benefield et al. (1980) Benefield et al. (1980) Benefield et al. (1980)

Photo-oxidation profile in AOP reactor The degradation profile of pollutant A, intermediate S, and sludge X in AOP reactor can be seen at Figure 2. Substrate A and X are converted into intermediate S and another stable end product. The initial concentration of A and sludge X entering 62

the AOP reactor is 10 g·l-1 and 10 g·l-1 respectively. Ninety percent of X and A, are converted to intermediate S. As increasing of residence time, the concentration of A and X decrease due to photo-oxidation. Using the given parameters, it may see that the concentration of A, S, and X in AOP reactor are 0.43, 1.47, 0.09 g·l-1 respectively, that will be fed to MBR. 10 Substrate A (g/L) Biomass X (g/L) Substrate S (g/L)

Substrate concentration (gram/liter)

9 8 7 6 5 4 3 2 1 0

0

1

2 3 4 5 6 7 8 Foto chemical reactor residence time (Hours)

9

10

Figure 2. Photo-oxidation profile in AOP reactor (r =0.1Ai=10 g·l-1, CS1=CSX=0 g·l-1, CX2=10 g·l-1, kX=1 h-1, kS=0.5h-1, a=0.9, b=0.9). The combination of AOP-MBR increased the cell decay to maintain the biomass concentration in acceptable level. Consequently, the recycled sludge must be hydrolyzed as low as possible. Using the given parameters as shown in Figure 2, the concentration of sludge leaving the AOP reactor CX1 is very low compare to the concentration of sludge enter the AOP reactor. The intermediate of S was simultaneously produced from degradation of A and hydrolysis of sludge. At low residence time S increased initially and decreased at longer residence time, the rate of intermediate S production is lower than degradation. It resulted in the accumulation of S in reactor. By increasing the residence time, the rate of S production was less than degradation, therefore the concentration of S decreased. The remaining S that is not degradated would be biologically oxidized in MBR. The maximum concentration of S in AOP reactor was 4.4 g·l-1. This value was obtained at AOP residence time of 1 hour. The concentration of A in AOP reactor depends on feed concentration, retention time and the kinetic constant. The relation of these parameters is shown in Figure 3. The important parameter that determine the depletion rate of substrate A is rate kinetic constant. However, this kinetic constant is intrinsic and can not be manipulated during the process operation. To attain the certain limit of minimum A concentration, it can proceed by increasing residence time or reducing the feed A concentration through dilution. In this model, A is assumed as recalcitrant chemicals that only degraded in AOP reactor but not in MBR. The CA1 will be equal to CA3 because no further degradation in MBR. This situation can be very critical to meet the substrate limit for wastewater discharge. Therefore the complete degradation of A in AOP reactor is preferable.

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10 kA=1, kA=1, kA=2, kA=2,

Substrate concentration (gram/liter)

9 8

CAi=5gr/L CAi=10gr/L CAi=5gr/L CAi=10gr/L

7 6 5 4 3 2 1 0

0

1

2 3 4 5 6 7 8 Foto chemical reactor residence time (Hours)

9

10

Figure 3. Profiles of substrate A concentration in AOP reactor. Sludge hydrolysis in AOP reactor The depletion of sludge concentration in AOP reactor is determined by several operational parameters; sludge hydrolysis rate constant (kX), recycle ratio (r), concentration of sludge from MBR (CX2), and residence time of AOP reactor. The relations between these parameters are presented in Figure 4 and Figure 5. The r and CX2 determine the amount of sludge entering AOP reactor. Technically, r can be used to control the concentration of sludge in MBR by manipulating Q2. When the concentration of sludge is higher than expected, the recycle flow rate of Q2, need to be increased, and vice versa. The higher recycle ratio and sludge concentration in MBR will proportionally increase the amount of sludge entering the AOP reactor. It has been noticed that r also directly determines the initial sludge concentration for photochemical degradation. These proved by the straight line profile of sludge concentration when it is plotted to r. The simulation on effect of sludge concentration in MBR (CX2) to the sludge concentration in AOP reactor is shown in Figure 4 (a). MBR sludge concentration of 6, 8, and 10 g·l-1 that recycled to AOP reactor (CX1) can be reduced to 0.26, 0.36, and 4.5 g·l-1 respectively.

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0.45 CX2=6 gr/L CX2=8 gr/L CX2=10 gr/L

0.4

kX=0.5 kX=1 kX=2 kX=4

0.8 0.7 Biomass concentration (gr/l)

Biomass concentration (gr/l)

0.35 0.3 0.25 0.2 0.15

0.6 0.5 0.4 0.3

0.1

0.2

0.05

0.1

0

0

0

0.2 0.4 Recycle ratio

0

0.2 0.4 Recycle ratio

(a)

(b)

Figure 4. Effect of sludge concentration in MBR and hydrolysis constant in various recycle ratio on sludge concentration in AOP reactor (CAi=10, CSi=0, CXi=0, kA=2, kS=0.5, τ1=10, a=0.9, b=0.9), (a) kX=1, (b) CX2=10. 1.5

2 r=0.05 r=0.1 r=0.15 r=0.2

1.8 1.6 Biomass concentration (gr/l)

Biomass concentration (gr/l)

Tau=2.5 Tau=5 Tau=7.5 Tau=10 1

0.5

1.4 1.2 1 0.8 0.6 0.4 0.2

0

0

0.2 0.4 Recycle ratio

0.6

(a)

0

0

5 Recidence time (Hours)

10

(b)

Figure 5. Effect of AOP reactor residence time in various recycle ratio to sludge concentration in AOP reactor (left graph), Effect of recycle ration on sludge concentration in various residence time of AOP reactor (right side). The sludge concentration in AOP reactor must be maintained as low as possible. This is meant to meet the objective of controlling the sludge concentration in MBR. Figure 4 and Figure 5 show that in wide range of operational parameters tested, the sludge can be reduced down to 0.5 g·l-1. The depletion of X in AOP reactor solely depends on sludge hydrolysis kinetic aspect. Figure 4(a) was run using AOP residence time of 10 hours. It showed that CX1 could be maintained low, under 1 g·l-1 for the CX2 in range of 5-10 g·l-1. Another important parameter is sludge hydrolysis reaction constant (kX). When comparing the CX2 in various range of kX 0.5-4 h-1, the CX1 is increased from 0.11 to 0.81 g·l-1.

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3.3 Membrane bioreactor biodegradation performance The main objective of MBR is to convert substrate S biologically to be more stable chemical. The substrates and sludge profile in MBR is shown in Figure 6. The concentration of A in bioreactor is similar to concentration of A in the outlet.Due to biodegradation of S that occur in MBR the concentration of S will decreased. Figure 6(a) shows the profile of S in various MBR retention time that is simulated using kinetic parameters of kd = 0.07 h-1, Y=0.1, µmax = 0.4 h-1, KS = 0.2 g·l-1. Using given parameters, the substrate S that is fed from AOP reactor of 1.83 g·l-1 could be reduced to 0.012 g·l-1 that is more than 99.9% removal. This value can be further reduced by increasing the residence time in MBR. 0.4

18 16 CS2(gr/L) CA2 (gr/L)

0.3

14 Sludge Concentration (gr/l)

Substrate concentration (gr/l)

0.35

0.25 0.2 0.15 0.1

10 8 6 4

0.05 0

12

2

2

0

4 6 8 10 MBR Residence time (hours)

2

4 6 8 10 MBR Residence time (hours)

(a) (b) Figure 6. Substrate concentration profiles in MBR ( r =0.4, CAi =10 g·l-1, CSi = CXi = 0 g·l-1, kh=2 h-1, kX=1 h-1, KS=0.2 h-1, a=0.9, b=0.9, kd=0.07 h-1, Y=0.1, µmax =0.4 h-1). In a biological wastewater treatment, the produced sludge is directly proportional to the amount of COD removed (CS1-CS3). Figure 6(b) shows the steady state sludge concentration in MBR. At high retention time, the sludge concentration is higher due to the increasing of substrate S converted to produce sludge. By using the parameters for Figure 6, the sludge concentration could be maintained in acceptable range of 8-15 g·l-1 for MBR operation. The bio-kinetic parameter is very important in order to meet the MBR objective, where bio-kinetic constant of µmax and KS directly affect the biodegradation rate of S. In this study, some ranges of µmax and Ks were applied to the calculation, where smaller µmax and larger KS mean less biodegradability. The effect of bio-kinetic parameter to substrate S biodegradation profile is presented in Figure 7. The result showed that within the calculation range the substrate S was biodegradable; the change on µmax in range of 0.4-0.8 h-1 and KS from 0.1-0.4 g·l-1 does not significantly affect the biodegradability of S within the high MBR residence time (5-10 h). The low µmax and high KS showed significant effect when low residence time (less than 4 hours) is applied. 66

It has been well known that a high F/M ratio may cause flux decline in MBR through promoting the emission of extra-cellular polymeric substances (EPS). In fact, EPS is known as one of the major membrane foulants in MBR. Under the high organic loading condition, forming and sludge bulking can also arise. The influence of increased actual F/M ratio in the AOP-MBR system needs to be studied further for practical use. The sludge concentration in AOP-MBR system is not sensitive to the biodegradability of organic compounds. Therefore the assumption that µmax and KS for all organic constituents are the same, might not affect the results significantly. Moreover, the sludge removal process in the AOP-MBR system can be dealt without the consideration of biodegradability if the influent does not contain extremely refractory chemicals. Through extensive testing of numerous variables in acceptable range, the critical parameters that most significantly affect the sludge concentration in MBR are CS1 and r. From Figure 8(a) it can be seen that increasing the substrate S concentration that entering the AOP reactor (CS1)is significantly affect the steady state concentration in MBR. This substrate is used as food for sludge and converts to more stable chemical and/or to produce the new cell. Increasing the CS1 from 0.5 to 2 g·l-1 will increase the sludge concentration from 4.2 to 20 g·l-1 when the residence time is equal to 10 hours. 0.12

0.7 UmaxA=0.4 UmaxA=0.6 UmaxA=0.8

0.6 Substrate S Concentration (gr/l)

Substrate S concentration (gr/l)

0.1

0.08

0.06

0.04

0.02

0

KS=0.1 KS=0.2 KS=0.3 KS=0.4

0.5

0.4

0.3

0.2

0.1

2

0

4 6 8 10 MBR Residence time (hours)

2

4 6 8 10 MBR Residence time (hours)

(a) (b) Figure 7. Substrate concentration (S) profiles in MBR ( r = 0.4, CAi = 10 g·l-1, CSi = CXi = 0 g·l-1, kh = 2 h-1, kX = 1 h-1, a = 0.9, b = 0.9, kd = 0.07 h-1, Y = 0.1, (a) KS = 0.2 h1 , (b) , µmax = 0.4 h-1) To maintain the sludge concentration in acceptable range, the manipulation of recycle ratio (r) was very applicable. Figure 8(b) shows the effect of recycle ratio on steady state sludge concentration. Reducing the sludge concentration could be achieved through increasing the recycle ratio. Using parameters that applied for simulation of Figure 8, it can be seen that by increasing the recycle ration from 0.1 to 0.4, the steady state sludge concentration can be reduced from 65 to 15 g·l-1. Increasing recycle ratio means, increasing of the returned sludge to AOP reactor.

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20

70 CS1=0.5 gr/L CS1=1 gr/L CS1=1.5 gr/L CS1=2 gr/L

18

60

Sludge Concentration (gr/l)

Sludge Concentration (gr/l)

16 14 12 10 8 6

r=0.1 r=0.2 r=0.3 r=0.4

50

40

30

20

4 10 2 0

2

0

4 6 8 10 MBR Residence time (hours)

(a)

2

4 6 8 10 MBR Residence time (hours)

(b)

Figure 8. Effect of MBR loading and recycle ration on sludge concentration in MBR in various MBR residence time. (kd=0.07 h-1, Y=0.1, µmax = 0.4 h-1, KS =0.2 g·l-1). CONCLUSIONS The results of this study show the biodegradation profile and effect of significant parameters to evaluate the performance of AOP-MBR system. The following conclusions could be drawn from present study: 1. The degradation of substrate A, S, and X in AOP reactor is well described using the proposed model. This photo-chemical oxidation is key stage in order to achieve the objective for zero excess sludge production. 2. The concentration of A and X in AOP reactor can be well controlled by manipulating the residence time. 3. By using parameters that is applied in calculation, the concentration of S in MBR can be maintained in very low level. The simulation on acceptable range of µmax and KS shows that within the calculation range the substrate S is well biodegradable. 4. Substrate S concentration at feed of MBR can significantly affect the steady state concentration in MBR but can be controlled by manipulation of recycle ratio. ACKNOWLEDGEMENT The authors would like to thank to Universiti Teknologi PETRONAS for support and funding this research project. REFERENCES Benefied L. D., and Randall C. W. (1980). Biological Process Design for Wastewater Treatment. Prentice-Hall, Inc., Englewood Cliffs, N.J. Egemen E., Corpening J., Nirmalakhandan N. (2001). Evaluation of an ozonation system for reduced waste sludge generation. Water Sci Technol, Volume 44 (2–3), Pages 445–452. Espulgas S. and Ollis D. F. 1993. Process integration development: Reactor kinetic models for sequential chemical and biological oxidation for water

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treatment. Chemical Oxidation Technologies for the Nineties IV, Technomic Publishing Company, Lancaster. Rosenberger, S., Witzig R., Manz W., Szewzyk U., Kraume M., (2000). Operation of different membrane bioreactors: experimental results and physiological state of the microorganisms. Water Sci Technol, Volume 41(10–11), Pages 269–77. Sakai, Y., Fukase T., Yasui H., Shibata M. (1997). An activated sludge process without excess sludge production. Water Sci Technol, Volume 36(11), Pages 163–70. Yoon, S. H. (2003). Important operational parameters of membrane bioreactorsludge disintegration (MBR-SD) system for zero excess sludge production. Water Research, Volume 37, Pages 1921–1931. Yasui, H., Nakamura K., Sakuma S., Iwasaki M., Sakai Y. (1996). A full-scale operation of a novel activated sludge process without excess sludge production. Water Sci Technol, Volume 34(3–4), Pages 395–404. Yoon, S. H, Kang I. J., Lee C. H. Fouling of inorganic membrane and flux enhancement in membrane-coupled anaerobic bioreactor. Sep Sci Technol 1999;34(5):709–24.

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NEMATODE PARASITES OF FISH AS AN INDICATOR OF POLLUTION OF SEA 1

Rafia Azmat, 2Shahina Fayyaz and 2Nasira Kazi

1

Department of Chemistry and 2National Nematological Research Center 1 Jinnah University for Women and 2 University of Karachi Karachi, Pakistan E: Mail:[email protected] ABSTRACT In this study we have tried to draw an attention to the impact of long - term metal contamination in the fishes and nematode parasites of fishes. Parallel analysis of heavy metals in muscles, gills, guts and livers and fish parasite were detected by atomic absorption Spectrophotometry. The bioaccumulation potential of heavy toxic metals like Pb, Cd, Hg, As, Zn and Fe was assessed in the Echinocephalus spp. and Ascaris spp. which are reported first time in Liza vaigiensis and Liza subvirdis from Karachi coast. The concentration of heavy metals compared with that of muscles, gills, guts and livers of fish which then subsequently compared with sea water collected from different coastal areas of Arabian Sea. Macroscopic lesions due to accumulation of metals might not always be apparent, but subtle disorder in several specific tissues likes gills tissues were observed. Concentration of Pb in gills was significantly higher as compared to other tissues of fish. These conditions may results in decreased resistance by the fish, causing spread of disease and parasitic infection. The high level of heavy metals accumulation in the Echinocephalus spp. and Ascaris spp within its host suggests that these nematode parasites are sensitive indicator of heavy metals in aquatic ecosystem. The higher concentration of metals in nematode parasites were compared with muscles of infected fish which may be attributed with the sharing of more burden of environmental pollution of sea by parasite due to continuous discharged of industrial wastage or oil spills containing high percentages of heavy metals. Key words: Nematode Parasite, Pollution, Metals, Fishes INTRODUCTION In environmental impact studies certain organisms provide valuable information about chemical state of their environment not through their presence or absence but through ability to concentrate environmental toxins within their tissues (Tenora et al., 1999 ; Ucman et al., 2001 and Bernud.,2001).More heavy metals burden like Pb, Cd, Cr and Ni in these parasites – host system were reported by Tenora et al (1999). Pollutants might promote increased parasitism in aquatic animals, especially fish by impairing the host‘s immune response or favoring the survival and reproduction of the intermediate hosts (Khan and Thulin., 1991). Parasites are naturally occurring organism ( Barus et al., 1999), attracting increasing interest as potential indicator of environmental quality due to variety of ways in which they respond to anthropogenic pollution (Barak and Mason., 1990).

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Goldstein et al., (1996) found that the concentrations of mercury in the liver of definitive host was higher but not significantly different from visible concentration. Borotheridge et al., (1998) reported that trout likely to be infected with parasites nematode, Eustrogylidies spp. due to the presence of Ni and Cu in fish. Trucekova et al., (2002) analyzed As, Cd, Cu, Pb and Zn in perch and tape worm Protocephalus perace and Acanthocephalus lucii, respectively which were higher in liver of fish. Similarly certain parasites, particularly intestinal Acanthocephalus of fish can accumulate heavy metals to concentration orders of magnitude higher than those in the host tissues. Parasitic cestode and nematode like Ligula intestinals and Philometra ova–ta, respectively were collected from cyprinid fish. The flesh muscle contains Pb, Cd, Hg and Cr (Tenora et al., 2000 and Olukova et al., 1997). Protocephelus percae and Acanthocephalus lucii were found in the polluted water fishes which contain heavy toxic metal like Pb, Cd, As, Cu and Zn. Investigation shows that parasitic infection increase significantly in the gills following exposure to a pollutant and this is supported by field data on other ciliates and monogeneans where evidence of pollution has been clearly demonstrated (Sures et al .,1997). Several types of pollutants, including domestic sewage, pesticides, polychlorinated biphenyls, heavy metals, pulp and paper effluents, petroleum aromatic hydrocarbons, acid rain, and others are known to effect marine life (Ucmann et al’., 2001). The purpose of the current study is to analyze the influence of oil/industrial waste discharging at Karachi coast and to evaluate the uptake of heavy metals by coastal fishes and their effect on different part of fishes. This paper will also discuss the parasitic infection due to heavy metals in fishes and persistent of nematode parasite in fishes as a bioindicators of heavy metal. RESULTS AND DISCUSSION Heavy metals analysis of seawater, fish and fish nematode parasites of fish under studied showed that Pb, As, Cd, Hg, Zn and Fe were detected. The levels of heavy metals were summarized in Tables 1- 2 and compared with international literature (Table 3) and found higher and approximately equal in muscles (Table 2 and 3) of the fish (Khansari et al., 2005). Results showed that heavy metals are more prevalent in the contaminated sites and they may be in higher concentration if continuous discharge were made in aquatic resources (Trucekova et a., 2002, Tariq et al.,1993 ). Having high density, they have more tendencies to accumulate in the tissue organs of animals as compared to essential micro and macronutrient ions (Azmat et al., 2006a). Concentration of heavy metals like Zn, As, Cd, Hg, Pb and Fe in fish organs which were reported in the Table 1 showing that these contaminates may be of great concern in places suffering from pollution caused by human activity (Svobodova et al., 1999). The worst parts of these metals are, once they build up in the body they can cause irreversible damage, also they alter the marine environment; support the growth of viruses and other microorganism including nematode parasites in fishes ( Azmat et al., 2006b ). Heavy metals concentration differed significantly (Table1-2) between the organs of fish and nematode parasite with level up to several hundreds folds. The high level of heavy metals accumulation in nematode parasites (Echinocephalus spp. and Ascaris spp) was compared with that of its host, suggest that nematode parasites are most sensitive indicator of heavy metals in aquatic ecosystem and they are persistent contaminated environment and by sharing more burden in their tissues, act as bioremediater for fish and help in the survival of fish with toxins. Atomic absorption

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spectroscopy of both nematode species(Echinocephalus spp. and Ascaris spp) showed that they contain very high concentration of heavy metals (Table 3) which was greater than concentration of heavy toxic metal found in muscle, liver, gills and guts showing that these nematode parasites can be used as bioindicators of heavy metal pollutants in fishes (Trucekova et al., 2002). Table 1 shows that concentration of Pb was higher in the gills. It may be due to the fact that gills are directly exposed to the sea water for exchange of gases during respiration while sea water contain high level of toxins (Table 1) which can accumulate within gills tissue (Chibani et al., 2001).The high concentration of Pb in gills may affects the respiration rate. The investigation suggests a relationship between Zn deficiency and increased nematode infections as the concentration of Zn in guts (Table 1) is less as compared to the nematode parasite and Zn is involved both in maintenance of gut structure and function (Gulfaraz and Ahmed., 2001). The lower concentration of Zn in fishes may be related with higher concentration of heavy metal Cd, higher as given by Environmental Protection Agency (EPA) which may be attributed with replacement of Zn with Cd due to chemical similarity. Cadmium derives its toxicological properties from its chemical similarity to Zn, an essential micronutrient for plants, animals and human. Cd as an ion affects on respiration and binders in exchange of gases (Gulfaraz and Ahmed., 2001). The concentration of Cd in the liver by far exceeded the concentration in the muscle tissue, for all investigated species. Cadmium is highly toxic and biopersistant and if an organism absorbs it remain resident for many years (Over decades for human) although it is eventually excreted (Gulfaraz and Ahmed; 2001, Canli et al., 1998). Cd in fish is absorbed both from the surrounding water by the gills, and from the food by digestion and these transported by the blood, mainly to the liver and kidney in these both organs Cd is bound to certain proteins. It was observed that fish specimen which showed highest concentration of heavy metal contain clusters of nematode parasites and the weight of fish was less as compared to those fishes in which metal concentration was not that much pronounced. The concentrations of mercury in the muscles of both fishes were higher as compared with other organs. Mercury is a heavy toxic metal due to its long lifetime in the atmosphere. Mercury is transported over a large distance and deposition plays a major role in the transfer of mercury from the atmosphere to surface water. The trace quantities of mercury is present in crude oil (Svobodova et al., 1999, Voegborlo et al., 1999 ) Fish accumulate substantial concentration of mercury in their muscle tissues and in this study it was 0.34 and 0.41 ( g g-1) for commercially important marine species. It is evident from the Table 2 that Liza vaigiensis and L. subvirdis contained lowest mercury level as compared to fish nematode parasites (Table 3). This indicates that metal accumulation is greater in nematode parasite due to its soft tissues. Fish are the single largest of mercury and arsenic (Khansari et al..,2005, Holden., 1973). CONCLUSION Investigation revealed that chronic exposure to pollutants over a period of time cause biochemical, physiological and behavioral host changes that ultimately influence the prevalence and intensity of parasitism while stress affects the population dynamics of infectious disease. Most heavy metals burdens in these parasites also indicate that fish nematode parasite may used as bioindicator of metal pollutants..

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ACKNOWLEDGEMENT Author is very thankful to HIGHER EDUCATION CMMISSION PAKISTAN for providing research travel grants to Jinnah University for Women of Pakistan for presenting research article at 12 ACC kim Maleshya Table 1. Heavy Metal Concentration (g g-1) in Common Edible Marine Fishes MUSCLE Cd 0.11±0.01 0.12±0.01 GILLS As Cd 0.118±0.0 0.19±0.01 5

Name of species Liza vaigiensis Liza subvirdis

Pb 0.28±0.01 0.29±0.01

As 0.18±0.01 0.21±0.01

Name of species Liza vaigiensis

Pb 0.45±0.01

Liza subvirdis

0.37±0.01

0.15±0.02

Name of species Liza vaigiensis Liza subvirdis

Pb 0.21±0.01 0.23±0.01

As 0.21±0.01 0.230.01

Name of species Liza vaigiensis Liza subvirdis

Pb 0.23±o.11 0.13±0.01

As 0. 24±0.01 O.12±0.01

0. 21±0.01 LIVER Cd 0.05±0.01 0.02±0.01 GUTS Cd 0.09±0.02 0.12±0.91

Hg 0.34±0.01 0.41±0.01

Zn 0.22±0.01 0.21±0.01

Fe 0.23±0.01 0.24±0.01

Hg 0.15±0.01

Zn 0.321±0.01

Fe o.24±0.01

0.23±0.01

0.332±0.01

0.32±0.01

Hg 0.12±.0.01 0.21±0.01

Zn 0.20±.01 0.31±0.01

Fe 0.23±0.01 0.32±0.01

Hg 0.21±0.01 0.15±0.01

Zn 0.11±0.01 0.11±0.01

Fe 0.23±0.01 0.21±0.01

Table 2. Bioaccumulation of Heavy Metal Potential (g g-1) in Nematode Parasite of Fish Nematode Echinocephalus spp. Ascaris spp

Pb 21±01 25±03

As 19±03 22±02

Cd 12±01 15±02

Hg 07±03 09±01

Fe 72±06 80±07

Table 3. Comparison of Present Values with International Data. Metals

Present work (muscle) (g g-1)

Literature value with Reference (g g-1)

Pb

0.28

As

0.18

Cd

0.19

Hg

0.34

Zn Fe

0.20 0.23

0.28 (Voegborlo.,1999) 0.0366 (Khansari et al.,2005) 0.16-32.3 (Attar et al.,1992 ) 0.128 (Khansari et al.,2005) 0.29 (Tariq et al.,1993) 0.0223 (Khansari et al.,2005) 0.29 (Voegborlo.,1999) 0.117 (Khansari et al.,2005) 2.0 (Sen et al.,1989) 5.0 (Sen et al.,1989

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Zn 30±12 32±11

REFERENCE 1) Attar,K.M., El-Faer, M.Z..Rawdah, T.N.,Tawabini, B.S., 1992. Levels of arsenic in fish from the Arabian Gulf. Marine pollution bulletin. 24,94-102 2) Azmat, R. .Rizvi, S.S. , Talat, R. and. Uddin, F. 2006a. Macronutrient found in some edible herbivorous and Carnivorous Fishes of Arabian sea., Journal of Biological Sciences.. 6, 301-304 3) Azmat, R.,Akhter, Y., Talat, R. and Uddin, F. 2006b. Persistent of Nematode parasites in presence Heavy of metals found in Edible Herbivorous Fishes of Arabian Sea. Journal of Biological Sciences..6, 282-285. 4) Barak, N., Mason, C.F. 1990. Mercury and lead in eels and roach: The effects of size, season and locality on Metal concentration in flesh and liver. The Science of Total Environment. 92, 249 – 256 5) Barus, V, Tenora, F. Kracmar, F. Proke, S. Dvoracek,, J. 1999. Microelement content in males and females of Anguillicola crassus (Nematoda: Dracunculodea). Helminthologia 36: 283 – 285. 6) Brotheridge, R.M.K.E.Newton and S.W. Evans.1998. Presence of a parasite nematode (Eustrongylidies sp.) in brown trout from a heavy metal contaminated aquatic ecosystem. Chemosphere. 37, 2941-34. 7) Bernud,S. 2001. The use of fish parasite as bioindicator of heavy metals in aquatic ecosystem: a review. Aquatic Ecology.35, 245-251 8) Canli,M., O.Ay.M.Kalay.1998.Metals of heavy metals(Cd,Pb,Cu andNi) in tissues of Cyprinus carpio, Barbus capito and Chondrostoma regium from the Seyhan River. Turkey. Turkish Journals of Zoology.22,149. 9) Chibani M., Ziólkowska M., A. Kijewska J. Rokicki. 2001.Pomphorrhynchus laevis parasite of flounder Platichthys flesus as a biological indicator of pollution in the Baltic Sea. Journal of Marine Biological Assessment. U.K. 81, 165-166 10) Goldstein, Rm, Brigham, Me, Stauffer, Jc 1996: Comparison of mercury concentration in liver, muscle and whole bodies, and composites of fish from the Red River of the North. Canadian Journal of Fish Aquatic Science. 53, 244. 11) Gulfaraz. M. and T. Ahmad 2001. Concentration level of heavy and trace metals in the fish and relevant water from Rawal and Mangal Lakes. Pakistan Journal of Biological Sciences. 5, 414 12) Holden,A.V. 1973.Mercury in fish and shellfish, a rewiew, Journal of Food Technology,8,1 13) Khan, R. A., J.Thulin. 1991. Influence of pollution on parasite of aquatic animals. Advance Parasitology. 30, 201-38. 14) Khansari,F.E., Khansari,M.G.and Abdollahi, M. 2005. Heavy metals content of canned tuna fish. Food chemistry.93,293 15) Olukova, D.K, S.I.Smith and M.O..Ilori, 1997. Isolation and characterization of heavy metals resistant bacteria from lagos lagoon. Folia Microbiology. 42, 441 – 4 16) Svobodova, Z, Du-Ek, L, Hejtma’nekm M, Vykusova, B, Mid R 1999: Bioaccumulation of mercury in various fish Species from Orlik and Kam K water reservoirs in the Czech Republic. Ecotox Environmental Safety 43, 231-236 17) Sures.B. H.Taraschewski, J. Rokicki. 1997. Lead and Cadmium contents of two cestodes Monoboyhrium wageneri and Bothricephalus scorpii, and their fish host. Parasitology Research. 83, 618-623

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18) Trucekova,L. V. Hanzelova, M.Spakulova.2002. Concentration of heavy metals and its endoparasites in the polluted water reservoir in Eastern Slovakia. Helminthologia 39:1-23 19) Tenora, F. , V. Barus, S. Kracmar, J. Dvoracek. 2000. Concentration of some heavy metals in Ligula intestinalis plerocercids (Cestoda) and Philomera ovata (Nematode) compared to some their hostes (Osteichthyes). Helminthologia 37, 15-18. 20) Tenora.,F V. Barusi, S. Kracmar, J. Dvoracek, J. Srnkova. 1999. Parallel analysis of some heavy metals concentration in the Anguillicola crassus (Nematode) and the European eel Anguilla anguilla (Osteichthyes). Helminthologia 36, 79-81. 21) Tariq,J.M.Jaffer and M.Ashraf.1993. “Heavy metal concentration in fish, shrimp, seaweed, sediment and water from Arabian Sea,Pakistan” Marine Pollution Bulletin ,26,644-678 22) Ucman, E, M. Vavrova, S. Zima, P. Kooinek, J. Pavelka, H. Zlamalova Gargo – Ova H 2001: Studies on the transfer of harmful substances from feed chicken tissues. Canadian Journal of Analytical Science spectrum. 46: 89 -95 23) Voegborlo R.B., A.M.E.Methnani and M.Z.Abedin, 1999. Mercury , Cadmium and Lead content of canned tuna fish. Food Chemistry,67,341-346.

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STUDY ON UTILIZATION OF ACTIVATED SLUDGE PROCESS FOR HEAVY METALS-CONTAINING WASTEWATER Soon-An Ong1,2, Eiichi Toorisaka1, Makoto Hirata1 and Tadashi Hano1 1

2

Department of Applied Chemistry, Oita University, Oita 870-1192, Japan School of Environmental Engineering, Northern Malaysia University College of Engineering, 02600 Arau, Perlis, Malaysia

ABSTRACT The biosorption of heavy metals by activated sludge could be used as an alternative method for heavy metal removal although they are toxic and often cause serious upsets in biological wastewater treatment plants. The aim of present work is to investigate the potential of employing activated sludge process, under sequencing batch reactor (SBR) operation, in the treatment of heavy metals-containing wastewater. It was observed that the addition of heavy metals in SBRs had caused deterioration in bio-oxidation processes by activated sludge microbes as shown in the reduction of specific oxygen uptake rate (SOUR). The result indicated that the activated sludge process could treat low concentration of heavy metals-containing wastewater. With the concentration of heavy metals lower than 5 mg/l in feed solution, the bio-oxidation processes by microbes only dropped about 20 %. Besides, the activated sludge process showed the ability to retain a huge amount of heavy metals through adsorption. Keywords: Activated sludge; SBR; Heavy metal; SOUR; sludge settled ability.

INTRODUCTION The effect of heavy metals to biological wastewater treatment processes has been studied in numerous works [ Dilek et al., 1991; Stasinakis et al., 2003; Lim et al., 2002; Ong et al., 2004; African & Yetis, 2003]. In general, heavy metals present in the influent at relatively low concentrations can be toxic to the biological processes and can prevent the effective degradation of organic wastes. The result is the discharge of poorly treated wastewater which cannot meet the effluents standards and could have adverse effects on the receiving waters [Nurdan et al., 1997]. Various treatment technologies have been developed for the removal of heavy metals from wastewater, depending on the concentration, such as precipitation of the metal hydroxide and filtration when higher concentrations are treated [Aziz et al., 2001; Kim et al., 2001]. Ion exchange using zeolites [Zamow & Murphy, 1992], clays [Reddy & Chinthamreddy, 2003] or ionic resins [Abollino et al., 2000; Yalcin et al., 2001] is generally employed when the range of contamination is low. However, these procedures often have significant disadvantages including incomplete metal removal, high chemical and energy consumptions, generation of toxic sludge, and are very expensive to operate at dilute concentrations that present in municipal wastewaters.

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An alternative method that has been suggested is to use microorganisms in biological wastewater treatment processes as an adsorbent for heavy metal removal. A number of studies have shown that some microbes present in activated sludge treatment systems produce extra-cellular polymers (ECPs) which can adsorbed and remove soluble metals from wastewater [Patterson, 1995]. The biosorption of heavy metals by microbes is a promising property with a potential for industrial use. In particular, with the growing scarcity and increasing value of some metals, this natural property of the microbes has also given importance to the study of this field from the view point of metal recovery [Sag et al., 1995]. The aim of this study is to investigate the feasibility of employing activated sludge process, under sequencing batch reactor (SBR) operation, in the treatment of heavy metals-containing wastewater. The heavy metals selected in this study were Ni(II), Zn(II), Cr(III) and Cd(II) because of their widespread industrial use and known toxicity to aquatic organisms. The influence of these heavy metals on the sludge settle ability, filamentous microbe population and oxygen uptake rate by microbes were investigated. MATERIALS AND METHODS Medium A synthetic wastewater was used throughout the experiments. The chemical composition of the simulated wastewater is shown in Table 1. The sucrose and peptone were used as source of organic carbons and was added to the medium to maintain COD in the range of 800-850 mg/l. Phosphate salts were used to provide both buffer action and as a phosphorous source for microbes. Table 1: Composition of synthetic wastewater Constituents Bacto-peptone

Concentration (mg/l) 188

Sucrose NH4Cl

563 344

MgSO4

49

FeCl3 KH2PO4 K2HPO4

11.3 250 318

Sequencing batch reactor (SBR) Four laboratory-scale reactors, 1, 2, 3 and 4 of dimensions 20 x 20 x 20 cm (L x W x H) with a total volume of 5 l were operated to simulate the activated sludge process under SBR operation. The SBR was operated in a cycle time of 6 hours. Each cycle consisted of 5 phases: FILL (0.5 h), REACT (3.5 h), SETTLE (1.0 h), DRAW (0.75 h) and IDLE (0.25 h). In each cycle, 3 l of synthetic wastewater was added in the SBRs during FILL period and the same amount of treated effluent was removed during DRAW period to maintain a residual volume of 2 l before the start of a new

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cycle. Effective mixing of the mixed liquor suspended solid (MLSS) in the reactor was achieved using submerged aeration stones during FILL and REACT periods. A temperature controller was used to keep the temperature constant at 25 oC throughout the experiments. The activated sludge seed was obtained from a municipal wastewater treatment plant that received no industrial wastewater. Then, the activated sludge was acclimatized in the laboratory by feeding it with a synthetic wastewater consisting peptone, sucrose, nutrients and buffer solution (Table 1).When the systems were acclimatized to the feed, Ni(II), Cr(III), Zn(II) and Cd(II) were added into SBR 1, 2, 3 and 4, respectively, at different concentrations. The concentrations tested for Ni(II) and Cr(III) were 5 mg/l and 10 mg/l, while 15 mg/l and 30 mg/l were used in the case of Cd(II). Four dosages were tested for Zn(II): 10 mg/l, 20 mg/l, and 40 mg/l. Analytical methods The treated effluents collected from the DRAW period in each cycle were analyzed for heavy metal concentration using ICPS-7000 (Shimadzu). The mixed liquor suspended solids (MLSS) and mixed liquor volatile suspended solids (MLVSS) concentrations followed the Standard Methods. The SOUR in each reactor was determined throughout the experiments by using the method described in previous study [Lim et al., 2002; Ong et al., 2004]. RESULTS AND DISCUSSION Effect of heavy metals on sludge settled ability In many cases, MLSS with poor settling characteristics has developed into what is known as bulking sludge condition, where MLSS floc does not settle well and floc particles are discharged in the effluent. As shown in Fig. 1, it was observed that the sludge settled ability in SBR 4 was poor compared to other reactors. Microscopic investigation revealed that the filamentous microbe growth rapidly in SBR 4 compared to others. This is because the SBR 1-3 were operated less than 30 days before the addition of heavy metals into the reactors whereas the SBR 4 was operated for more than 50 days. The continual use of readily biodegradable substrates (sucrose and peptone) as the source of carbon led to a gradual increase of filament abundance and caused activated sludge bulking in SBR 4. As a result, the sludge settling gradually deteriorated as shown in the increase of SVI (up to 220 ml/g). After the addition of heavy metals, the population of filamentous microbes reduced and cause a rapid decrease in the size of activated sludge flocs in SBRs. The increase of sludge settled ability had increased the sludge accumulation in the reactors. As shown in Fig. 2, the MLSS in SBRs increased with the addition of heavy metals that caused the deterioration of filamentous microbe population. Filamentous microbes are believed to form a ‘backbone’ of activated sludge flocs, on which floc-forming bacteria are fixed by means of extra-cellular polymers [Patterson, 1995]. Shuttleworth and UnZ (1991) reported that the floc-forming microorganism, Z.ramigera, was less sensitive to metal toxicity than filamentous microorganisms. This phenomenon is probably due to the fact that filamentous microorganisms extend trichomes outward from activated sludge flocs, into the bulk water. In this way, they come into contact with wastewater constituents, including toxic compounds, more readily than microorganisms embedded in the flocs.

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250

SVI (ml/g)

200 SBR 1 [Ni(II)]

150

SBR 2 [Cr(III)] SBR 3 [Zn(II)]

100

SBR 4 [Cd(II)] 50 0 0

5

10

15

20

30

40

Heavy Metals Concentrations (mg/l)

Fig. 1 Effect of heavy metals on sludge settled ability in SBRs

M LS S Concentrations (m g/l)

14000 12000 10000

SBR 1 [Ni(II)] SBR 2 [Cr(III)]

8000

SBR 3 [Zn(II)]

6000

SBR 4 [Cd(II)]

4000 2000 0 0

5

10

15

20

30

40

Heavy Metal Concentrations (mg/l)

Fig. 2 MLSS concentration in SBRs with and without the addition of heavy metals Heavy metal removal by SBRs Fig. 3 show the amount of heavy metal could be retained by activated sludge in SBRs. Above 50 % of heavy metal were removed except Ni(II) for the dosages of heavy metal less than 20 mg/l in feed solution. As the MLSS concentration in SBRs increased, it would increase the adsorption sites and subsequently increased the amount of heavy metals retain in the reactors. For SBR 1, 2 and 3 which treating Ni(II), Cr(III) and Zn(III), respectively, the heavy metal removal efficiencies didn’t show significant drop although the concentration of heavy metals were increased twice in feed solution. One of the reasons could be due to the increase of MLSS accumulated in SBRs. However, the percentage of heavy metals removal cannot be explained by activated sludge adsorption based on the maximum adsorption capacity according to Langmuir isotherm model. The adsorption capacity of activated sludge in SBRs before and after operation was different due to the change of sludge age. After 79

the addition of heavy metals, very little sludge wastage during DRAW period due to good sludge settled ability in the reactors. This implied that the sludge age became longer resulting in greater metal uptake by activated sludge. Extracellular polymeric substances (EPS) are reported to be actively involved in the biosorption of metals to activated sludge. EPS, which are secreted in part by micro-organisms during growth, consist of various organic substances such as polysaccharides, uronic acids, proteins, nucleic acids and lipids. The actual attachment of the metal ions on the cellular surface may include physical adsorption, ion exchange, complexation or chemical adsorption. Cellular surfaces consist of cationic and anionic exchange sites such as amino, phosphoryl, sulfydryl and carboxylic groups [Frolund wt al., 1995; Chang et al., 1995; Brown & Lester; 1982; Cheng et al., 1975]. 90 80 % Metal Removal

70 60 50

SBR 1 [Ni(II)]

40

SBR 2 [Cr(III)]

30

SBR 3 [Zn(II)]

20

SBR 4 [Cd(II)]

10 0 5

10

15

20

30

40

Heavy Metal Concentrations (mg/l)

Fig. 3 Heavy metal removal by activated sludge in SBRs Effect of heavy metal on specific oxygen uptake rate (SOUR) In order to investigate the effect of heavy metal on the activity of microbes, SOUR study (Fig. 4) was carried out throughout the experiment. It was observed that the addition of heavy metals had caused the decrease of bio-oxidation processes carried out by microbes as shown in the slow down of oxygen uptake rate. The SOUR decreased above 50 % after the addition of 10 mg/l Cr(III) and Ni(II) into SBRs. Generally, the increase of heavy metal concentration had enhanced the inhibitory effect and subsequently the bio-oxidation processes carried out by activated sludge microbes was reduced. In the case of Zn(II), the increase of SOUR value implied the ability of activated sludge microbes to tolerate with the toxic effect of Zn(II) after acclimatized with the Zn(II)-containing wastewater. The SOUR had improved after the increase of Zn(II) dosages from 5 to 40 mg/l. As compare to Cr(III), Ni(II) and Cd(II), the addition Zn(II) showed only a slightly inhibitory effect on the activity of activated sludge microbes.

80

SOUR (mgO2/gMLSS.h)

70 60 50 SBR 1 [Ni(II)] 40

SBR 2 [Cr(III)] SBR 3 [Zn(II)]

30

SBR 4 [Cd(II)]

20 10 0 0

5

10

15

20

30

40

Heavy Metal Concentrations (mg/l)

Fig. 4 Effect of heavy metals on SOUR CONCLUSIONS Based on the results obtained, the following conclusions can be drawn: The addition of heavy metals deteriorated the bio-oxidation processes carried out by microbes as shown in the reduction of oxygen uptake rate. Among of the heavy metals, the addition of Zn(II) only caused slightly inhibitory on the activity of activated sludge microbes. The population of filamentous microbes was reduced significantly in the presence of heavy metals compared to floc-forming microbes. The decrease of filamentous microbes would enhance the sludge settled ability in SBRs and subsequently increase the amount of activated sludge accumulation in the reactors. The activated sludge able to retain a huge amount of heavy metals especially for Zn(II), Cr(III) and Cd(II)-containing wastewater. The result indicated that the activated sludge process could treat low concentration of heavy metals-containing wastewater. With the concentration of heavy metals lower than 5 mg/l in feed solution, the bio-oxidation processes by microbes only dropped about 20 %. REFERENCES A.S. Stasinakis, N.S. Thomaidis, D. Mamais, E.C. Papanikolaou, A. Tsakon, T.D. Lekkas (2003). Effects of Cr(VI) addition on the activated sludge process. Wat Res, 37, 2140–2148. B. African, U. Yetis (2003). Nickel sorption by acclimatized activated sludge culture. Wat Res, 37(14), 3508-3516. B. Frolund, T. Griebe, P.H. Nielsen (1995). Enzymatic activity in the activated sludge floc matrix. Appl Microbiol Biot, 43, 755–761.

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C. Kim, Q.H. Zhou, B.L. Deng, E.C. Thornton, H.F. Xu (2001). Cr6+ reduction by hydrogen sulfide in aqueous media: stoichiometry and kinetics. Environ Sci Tech, 35, 2219–2225. D. Chang, K. Fukushi, S. Ghosh (1995). Simulation of activated sludge cultures for enhanced heavy metals removal. Water Environ Res, 67, 822-827. F.B. Dilek C.F. Gokcay, U. Yetis (1991). Effects of Cu(II) on a chemostat containing activated sludge. Environ Tech, 12, 1007–1016. H.A. Aziz, N. Otham, M.S. Yusuff, D.R.H. Basri, F.A.H. Ashaari, M.N. Adlan, F. Otham, M. Johari, M. Perwira (2001). Removal of copper from water using limestone filtration technique. Determination of mechanism of removal. Environ Int, 26, 395– 399. J.W. Patterson (1995). Industrial wastewater treatment technology, Butterworth Publishers, Stoneham, p. 467. K.L. Shuttleworth, R.F. Unz (1991). Influence of metals and metal speciation on the growth of filamentous microorganisms. Wat Res, 25, 1177–1186. K.R. Reddy, S. Chinthamreddy (2003). Sequentially enhanced electrokinetic remediation of heavy metals in low buffering clayey soils. J Geotech Geoenviron, 129(3), 263–277. M.H. Cheng, J.W. Patterson, R.A (1975). Minear. Heavy metals uptake by activated sludge. J Water Pollut Control Fed, 47, 362-376. M.J. Brown, J.N. Lester (1982). Role of bacterial extracellular polymers in metal uptake in pure bacterial culture and activated sludge-II Effects of mean cell retention time. Water Res, 6, 1549-1560. M. Sezgin, D. Jenkins, D.S. Parker (1978). A unified theory of filamentous activated sludge bulking. J Water Pollut Control Fed, 50, 362-380. M.J. Zamow, J.E. Murphy (1992). Removal of metal-cations from water using zeolites. Sep Sci Tech, 27(14), 1969–1984. O. Abollino, M. Aceto, C. Sarzanini, E. Mentasti (2000). The retention of metal species by different solid sorbents. Mechanisms for heavy metal speciation by sequential three column uptake. Anal Chim Acta, 411 (2000), 223–237. P.E. Lim, S.A. Ong, C.E. Seng (2002). Simultaneous Adsorption and Biodegradation Processes in Sequencing Batch Reactor (SBR) for Treating Copper and CadmiumContaining Wastewater. Wat Res, 36(3), 667-675. S.A. Ong, E. Toorisaka, M. Hirata, T. Hano (2004). Effects of nickel(II) addition on the activity of activated sludge microorganisms and activated sludge process. JHM, 113(1) (2004), 111 – 121.

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S. Yalcin, R. Apak, J. Hizal, H. Afsar (2001). Recovery of Cu2+ and Cr3+/6+ from electroplating-industry wastewater by ion exchange. Sep Sci Tech, 36(10), 2181– 2196. Y.B. Nurdan, O. Tulay, O. Onder (1997). Combined effects of Cu2+ and Zn2+ on activated sludge process. Wat Res, 31(4), 699-704.

Y. Sag, T. Kutsal (1995). Biosorption of heavy metals by zoogloea ramigera: use of adsorption isotherms and a comparison of biosorption characteristics. Biochem Eng J, 60 (1995), 181-188.

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A MODEL FOR THERMAL CONDUCTIVITY OF ARTIFICIAL METHANE HYDRATE SEDIMENT SAMPLE Tomoya Tsuji1, Toshihiko Hiaki1, Michica Ohtake2, Taro Kawamura2, Takeshi Komai2, Seong-Pil Kang3 1

College of Industrial Technology, Nihon University 1-2-1 Izumicho, Narashino 275-8757 Japan 2 National Institute of Advanced Industrial Science and Technology 16-1 Onogawa, Tsukuba 305-8569 Japan 3 Korea Institute of Energy Research 71-2 Jang-dong, Yuseong-gu, Daejeon, 305-343 Korea ABSTRACT Thermal conductivity was measured for artificial sediment samples composed of natural sand, methane hydrate, and the void saturated with water and methane by use of an apparatus based on a hot disk transient method at 10 MPa and 278 K. To predict thermal conductivity, a universal model was empirically proposed by considering the equivalent electric circuit such as series, parallel and distributed connection. The model showed a good reproducibility for the experimental data, and the characteristic dimension in the model would be an expression for morphology of the sediment sample. Keywords: Methane hydrate, Thermal conductivity, Hot disk transient method , Morphology, Theoretical model INTRODUCTION Methane hydrate is one of clathrate compound, that is, a guest molecule, methane, was trapped in cage of water molecules (Sloan, 1990). In Japan, methane hydrate is paid much attention as a new energy resources, because a large amount of methane hydrate would be existed in deep seabed near the southern coast of Honshu island, Japan. Now, a national project has been promoted by Japan Oil, Gas and Metals National Corporation (JOGMEC), and the Ministry of Economy, Trade and Industry, Japan (METI). Therefore, many researchers intensively investigate to recover methane hydrate from sediment in the deep seabed, and measured various physical properties of sediment containing methane hydrate. (Kawamura et al., 2003) In this study, thermal conductivity was measured for artificial sediment samples composed of natural sand, methane hydrate, and the void saturated with water and methane at 10 MPa and 278 K. From the viewpoint of morphology, a universal model was proposed to predict the thermal conductivity.

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EXPERIMENTAL Sample preparation Artificial sediment samples composed of natural sand, methane hydrate, and the microscopic void saturated with water or methane (Kawamura et al., 2003; Yamamoto et al., 2004). The natural sand was obtained from an actual sediment picked up from seabed in offshore of Tokai district, Japan. Prior to the sample preparation, the sand was dried for 24 hours at 383 K. Methane hydrate employed was artificial one, and it was macroscopically powder. The powder of methane hydrate was prepared from crashed ice and methane in a high pressure vessel. In the preparation, the crushed ice was loaded into the vessel, and successively pressurized with methane up to 10 MPa at 271 K. The pressure and the temperature were maintained for 3 days, and then the powder of methane hydrate can be obtained. The artificial sediment sample was mold to be a pellet by compression. Therefore, the powder of methane hydrate and the dry sand vigorously mixed each other, and loaded into a stainless steel mold at 170 K. The mixture was pressed by a stainless steel rod up to 30 MPa. The diameter of the sample pellet was about 30 mm, and the thickness about 15 mm. Thermal conductivity measurement Thermal conductivity was measured by use of an apparatus based on a hot disk transient method. The equipment and the procedure have been already reported previously (Yamamoto et al. 2004). After attaching disk probe onto the sample pellet, the microscopic void, in the sample, was saturated with water or methane at 10 MPa and 278 K. Pulse response of temperature was measured at the same pressure and temperature. According to Gustafsson (1991), the pulse response of temperature, T,is given by: W T ( )  2 / 3 D( ) (1)  r whereis thermal conductivity, W electric power supplied, r radius of the sample pellet. D(t) is a characteristic function with respect to non-dimension time, . The non-dimension time was given by:  1/ 2 1/ 2  t (2) r where  is thermal diffusivity, and the physical meaning is given by:   (3) Cp where Cp and  are isobaric heat capacity and density. However, the thermal diffusivity cannot be evaluated theoretically. In the measurement, assuming the value of , T() and D() were plotted with respect to . Then, the thermal diffusivity was optimized until under the linearity was observed among T() and D() as shown in eq. (1). RESULTS AND DISCUSSION Characterization of artificial sediment sample Prior to the measurement, the sample was characterized with three parameter, void fraction, porosity, and hydrate fraction. 85

Void fraction, , is defined as volume fraction without sand and hydrate:  f (4) where f is volume fraction of fluid. As shown in eq. (4), in this study, the void fraction is equal to the volume fraction of water or methane. Porosity, , is defined as total volume fraction without sand:   1  s (5) where s is volume fraction of sand. Methane hydrate fraction, xh, is defined as volume fraction of methane hydrate without fluid: h   xh   (6) s  h 1   where h is volume fraction of methane hydrate. Figure 1 shows the composition of the sample pellet prepared. In this study, two samples with the same composition were prepared. One was for the measurement saturated with water, and the other with methane. As shown in the figure, the volume fractions were distributed around f=0.400. However, the methane hydrate fraction was from h / (h +s )=0.00 to 1.000.

278 K 10MPa exp.

Sand

Methane sat. Water sat. calc. (This work) Mathane sat. Water sat.

Thermal Conductivity  [J/s m K]

Hydrate 2

Fluid

1

0

Figure 1 Thermal conductivity of sediment sample saturated with water or methane Thermal conductivity of artificial sediment sample Figure 1 shows the thermal conductivity of the sample saturated with water or methane at 10MPa and 278 K. Figure 2 is a projection onto hydrate – sand plane in Fig. 1. In the figure, the horizontal axis corresponded to the methane hydrate fraction. Table 1 lists the literature data of the thermal conductivity for each component. (Yamamoto et al., 2004; Cook, 1983) Since the data cannot be coincident in the literatures, the thermal conductivity of sand was not listed. For the sample saturated

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with methane, the thermal conductivity was linearly decreased with the methane hydrate fraction. The intercept at xh=1.000 seemed to be the averaged value for methane and methane hydrate. Otherwise, for the sample saturated with water, the tendency had been changed at a certain methane hydrate fraction. Up to xh=0.400, the thermal conductivity was linearly decreased with the methane hydrate fraction. However, the value was maintained to be constant, and it was also similar to the averaged one for water and methane hydrate. Proposal of a generalized model for thermal conductivity of the three components To predict the thermal conductivity, a universal model was considered in this study. Generally, models for thermal conductivity, of the three components, were classified into three types, series, parallel (Kasubuchi, 1982; Mochizuki et al., 1998), and distribution one (Dhama-Wardana, 1983; Matsubayashi et al., 1998). Figure 3 shows the equivalent electric circuits for the three models. For the series model, the thickness is proportional to the volume fraction of each component. Then, the overall thermal conductivity is given by: 1 s h  f    (7)   s h  f

Thermal conductivity  [J/m s K]

where  is the overall thermal conductivity, s,h, and f are that for sand, methane hydrate, and fluid, respectively. Similarly, for the parallel model, the effective area is proportional to the volume fraction. Then, the overall thermal conductivity is given by:   s s  h h   f  f (8) For distribution model, the thermal conductivity is empirically given by:    s s hh  f f (9) 278 K, 10 MPa Eq. (9) can be converted as follows: exp. ln    s ln  s   h ln  h   f2 ln  f Methane sat. Water sat. (10) Therefore, in any case, the overall thermal conductivity given by the averaged value of 1/, , and ln for series, parallel, and 1 distribution model, respectively. In this calc. study, a generalized model was empirically This work proposed. Regardless of the equivalent electric circuit, the thermal conductivity is given by: n n n 0 n   s  s   h  h   f  f (11) 0 20 40 60 80 100 xh [%] where n is a characteristic dimension Figure 2 Thermal conductivity and proposed in this study. Therefore, n=-1 methane hydrate fraction sediment sample correspond to perfect series model, and n=1 (10MPa and 278 K) to perfect parallel. In other words, the sign of characteristic dimension is thought to be an expression for morphology of the

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sediment sample. In this study, the characteristic dimension assumed to be constant Tabel 1 Thermal conductivity of components

i [J/s･m･K]

Water 0.567

Methane 0.043

Methane hydrate 0.450

for all sediment samples. Then, the characteristic dimension, n, and the thermal conductivity of sand, s, were optimized by using the thermal conductivity data saturated with water, and that with methane at xh=0.000. Other parameters, thermal conductivity of methane hydrate, methane and water, have been already listed in Table 1. Consequently, the optimized values, n=0.01199 and s=9.679 J/m･s･K were obtained. Considering the sign of the characteristic dimension, the layer of the sample would have a slight tendency like series model. In addition, the optimized value of the thermal conductivity for sand was similar to that of rock. Using the optimized n and s, the thermal conductivity was calculated in the whole range of composition. Figs. 1 and 2 are typical illustration of the calculation. As shown in the figure, the universal model showed a good reproducibility for the experimental data. s

h

f

s h f Series

Parallel

ls l+ h l+ f l

As A+ h A+ f A

Distribution

Figure 3 Conventional models for thermal conductivity

CONCLUSION Thermal conductivity was measured for artificial sediment samples composed of natural sand, methane hydrate, and the void saturated with water and methane by use of an apparatus based on a hot disk transient method at 10 MPa and 278 K. Conventionally, the thermal conductivity, of multi component system, has been converted to the equivalent electric circuit such as series, parallel, and distribution model. In this study, a new model was empirically proposed. Though the model was simple and ease in calculation, it may be substituted for conventional models. Especially, the characteristic dimension is thought to be an expression of the morphology in the sediment sample. The model has a possibility to apply the other transport phenomena.

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REFERENCES Sloan Jr., E. D., 1990; Clathrate Hydrates of Natural Gases, Marcel Dekker, New York, 24-44 Kawamura, T., K. Ohgata, K. Higuchi, J. H. Yoon, Y. Yamamoto, T. Komai, H. Haneda, 2003; Dissociation of Pellet-Shaped Methane-Ethane Mixed Gas Hydrate Sample, Energy and Fuel, 17, 614-618 Yamamoto, Y., T. Kawamura, M. Ohtake, T. Komai, F. Nakagawa, T. Tsuji, Y. Tsukada, 2004; Proceedings of The 14th International Offshore and Polar Engineers Conference Gustafsson, S. E., 1991; Transient Plane Source Techniques for Thermal Conductivity and Thermal Diffusivity Measurement of Solid Materials, Sci. Instrum., 62, 797804 Cook, J. G., D. G. Leaist, 1983; An Exploratory Study of the Thermal Conductivity of Methane Hydrate, Geophysical Res. Lett., 10, 397-399 Kasubuchi, 1982; Heat Conduction of Soil, Bul. Natl. Inst. Agric. Sci. Ser. B, 33, 1-54 Mochizuki, H., T. Miyazaki, M. Nakano, 1998; The Effect of Salts on Thermal Conductivity of Toyoura Sand, Trans. of JSIDRE, 198, 41-46 Dhama-Wardana, 1983; Thermal Conductivity of the Ice Polymorphs and the Ice Clathrate, J. Phys. Chem., 87, 4185-4193 Matsubayashi, O., R. N. Edwards, 1999; Relationship between Electrical and Thermal Conductivity for Evaluating Thermal Regime of Gas Hydrate Bearing Sedimentary Layers, ANN. N. Y. Sci., 912, 167-172

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APPLICATION OF THE EXCESS CARBON DIOXIDE PARTIAL PRESSURE (EpCO2) FOR ASSESSMENT OF THE TROPHIC STATE OF SURFACE WATER IN SOME VIETNAMESE RIVERS Trinh Anh Duc1, Choi Sung-Uk2, Nguyen Huong Giang1, Vu Duc Loi1, Le Lan Anh1 1

A18-Institute of Chemistry, Vietnamese Academy of Science and Technology, Hanoi, Vietnam 2 School of Civil & Environmental Engineering, Yonsei University, 139 Shinchondong, Seodaemun-gu, Seoul, 120-749, Korea 1 Tell: +84-4-8361281; Fax:+84-4-8361283 E-mail: [email protected]

ABSTRACT It is the first time in Vietnam, excess carbon dioxide partial pressure (EpCO2) was used to assess the trophic state of surface waters. The assessment of EpCO2 in the anthropogenic impacted rivers showed a considerable production of dissolved carbon dioxide at concentrations up to two orders of magnitude higher than pressure. Such pressures (EpCO2) are expected in polluted environments where biodegradation of organic matter overwhelms primary production. A number of factors linked to field monitoring and laboratory measurements clearly indicate a deterioration of water quality due largely to domestic wastewater impact from Hanoi and moreover no self cleansing process taken place in the river water. Key words: pH; Alkalinity; EpCO2; Urbanization, Photosynthesis, Respiration, Vietnam INTRODUCTION Rapid urbanisation and fast economic development in Vietnam has led to dramatic degradation of the environment and increased health risks due to inefficient processing of the increased burden of liquid and solid wastes (Trinh et al., 2006). Several examples of this are the Nhue River, the To Lich River, and the Day River flowing in the populous lowland delta in the northern part of Vietnam (Fig. 1). Recently, imminent consequence of the environmental deterioration has drawn environmentalists to investigate the impact of the anthropogenic activity intensification to the trophic condition of the regional waters. However, the assessment and evaluation procedures, especially to the rivers and streams, are not coherent and explicit. Conflicting results have always been found due to the nonlinearity of hydrological systems and the applied assessment protocols. The choice of specific trophic indicator which is easily assessed, regional-wide applicable, and most important to reflect the whole aquatic environmental condition is needed. Thus, partial carbon dioxide pressure as the significance of trophic and pollution state in tropical rivers is considered in this study. Indeed, information on the variations in partial pressure of dissolved carbon dioxide (CO2) in river waters is important in relation to studies of inorganic carbon equilibria within rivers (Kempe, 1982). The studies of dissolved CO2 in natural waters provide

90

an important indication of the balance between: (1) photosynthesis and respiration by biota; (2) carbon dioxide transfers at the air-river water interface; and (3) precipitation as solid phases such as calcium carbonate within the water body or at the streamstream bed interface (Howard, 1984; House et al., 1989; Maberly, 1996; Hartley et al., 1996). Such patterns are of wide environmental importance: for example, with regards to climate variability effects on water quality (Neal et al., 1997b), global carbon fluxes (Hope et al., 1994), and the recovery of rivers to reduced nutrient loads from sewage works (House and Denison, 1997). Measurements of dissolved CO2 are infrequent in environmental studies and general patterns of behaviour are now only becoming apparent. This paper considers the variations in the partial pressure of CO2 in relation to other water quality parameters and, furthermore, to the anthropogenic impacts to the major rivers in the Red River delta, northern part of Vietnam. The work is provided to further understanding of carbon dioxide generation and consumption in riverine environments at a regional scale and to act as a nucleus for further study at national and Southeast Asian levels. STUDIED SITES AND ANALYTICAL METHODOLOGY The data presented here are based the monthly surveys taken as part of the FrenchVietnamese Assessment programme2 for 4 rivers the Red, To Lich, Nhue and Day Rivers around Hanoi, capital city of Vietnam, in two periods 2001-2004 and 20062009. Total 9 sampling sites (named as R, N1, N2, N3, NT1, NT2, TL, D, and DN) located at critical points along the river reaches for evaluating diffuse and point sources were selected (fig.1). The descriptions of the hydrology, water quality and biology of the regional rivers can be found in Quynh et al. (2006). Details of the sampling sites and analytical methodologies used are described in Trinh et al. (2006) and Trinh et al. (2007). THEORY OF EpCO2 IN ASSESSMENT OF TROPHIC CONDITIONS In water, dissolved CO2 provides an indication of the balance between photosynthesis and respiration by biota. Carbon dioxide also transfers from the water column to the atmosphere as CO2 gas and precipitation as, for example, calcium carbonate minerals and in the process remove phosphate from solution and act in part as a self cleansing mechanism within the river (House, 1989; Maberly, 1996; Hartley et al., 1996; Neal, 2001). Dissolved CO2 can be used as powerful indicator of trophic state of the studied river (Neal et al., 1998b). Dissolved CO2 has not been directly determined in this study. However, as introduced by Neal et al. (1998a), the excess carbon dioxide partial pressure (EpCO2) is used as the alternative for dissolved CO2 as that this parameter can be easily calculated from the pH and Alkalinity which are standard determinands in environmental studies. In this study, we applied the following formula (Neal et al., 1998a).  0,95 * Alk  *10 6 pH EpCO2  6,46  0,0636 * t o C 2

Programme de recherches Franco Vietnamien sur la pollution des eaux en zone urbaine’’ between Centre National de Recherches Scientifiques, CNRS, France and Vietnamese Academy of Science and Technology; http://www.waterprogfrvn.org.vn 91

Fig.1: Map of the studied area

For this equation, alkalinity (Alk) is that which corresponds to the ‘normal’ measurement of bicarbonate alkalinity expressed in eq/l units and toC is temperature (oC). While not as accurate as some direct methods of determination, the advantages of this alternative procedure are (a) such data are extensively available for analysis, (b) these procedures can be undertaken with ease using standard electrometric and titrimetric laboratory equipment if care is taken, and (c) equipment costs and training times are relatively low. There are five potential errors contained within the approach. 1. The equation is built from chemical equilibria in water which are not independent from temperature. 2. The equation is the product of thermodynamic constants defined in terms of chemical activities and needs to be corrected for the effects of ionic strength. 3. The equation does not allow for the effects of complexes such as CO32-, CaHCO3-, CaCO30 and CaOH- which can be prevalent in higher pH waters. 4. pCO2 varies with meteorological conditions and altitude. 5. Other ions such as organic acids and Al contribute to the titration practice. RESULTS AND DISCUSSION Spatial changes of EpCO2 and other determinands Patterns in EpCO2, pH, alkalinity, dissolved organic carbon (DOC), and nutrient species (NH4 and PO4) at sampling sites are shown in table 1. Median values are presented to reduce the influence of outlier points and the sampling sites are ordered from north to south. Generally, each site exhibits a large range in EpCO2 values but all high above the saturation with respect to the atmosphere. The data show a broad increase in nutrient concentrations and EpCO2 towards Hanoi city. The highest EpCO2, DOC, NH4 and PO4 levels occur at the TL site. The levels in southern sites are also higher than in northern sites. This corresponds to increases in pollutant levels from the intact northern area to the urban and industrial areas in the center of the studied region and the polluted water from central zone flows southward. At site TL

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the EpCO2 reaches as high as 2 orders of magnitude. Further south, the NT1, NT2, and DN show gradual decreases in nutrients, DOC and EpCO2. Especially, similar patterns of EpCO2 are found in the Day River (D and DN) during 2006-2007 and in the Nhue River (NT1 and NT2) during 2002-2003 whereas EpCO2 levels were expected to be lower at D and DN than at NT1 and NT2. This observation can be explained by the increase of pollution over time (from 2002 to 2006). Besides, the overexploitation of limestone for cement production in upstream watershed of the Day River could also increase dissolved CO2 in water. Table 1: Median, Mean, Min-Max of determinands at sampling sites Points EpCO2 pH Alkalinity PO4 NH4 10.72 7.54 122 0.01 0.05 R

N1

N2

N3

TL

NT1

NT2

D

DN

15.18 2.91- 73.70 9.4 14.67 2.59-82.80 10.42 21.4 4.59-93.16 16.22 26.5 5.72-83.75 46.8 42.97 3.15-96.16 16.22 20.45 2.04-44.45 25.83 41.53 1.68-109.7 20.23 31.48 9.77-73.88 23.11 36.13 2.80-88.39

7.56 6.74 - 8.15 7.58 7.58 6.69-8.20 7.3 7.38 6.64-7.98 7.3 7.29 6.70-7.87 7.28 7.29 6.67-8.10 7.3 7.37 6.74-8.50 7.2 7.26 6.40-8.53 7.32 7.2 6.47-7.66 7.2 7.19 6.60-8.11

125.7 122.0-152.5 122 127.7 122.0-152.0 134.2 136.4 122.0-170.8 140.3 149.0 122.0-195.2 341.6 310.9 134.2-402.6 170.8 168.9 122.0-244.0 170.8 174.3 122.0-280.6 134.2 137.26 103.7-170.8 137.25 139.79 122-158.6

0.05 0.001-0.58 0.01 0.04 0.002-0.25 0.07 0.1 0.007-0.58 0.11 0.19 0.03-1.46 1.75 1.59 0.04-3.30 0.37 0.44 0.04-1.56 0.24 0.36 0.016-1.12 0.31 0.35 0.06-0.91 0.32 0.35 0.10-0.58

0.11 0.01-0.73 0.05 0.11 0.002-0.81 0.41 0.64 0.11-2.13 0.82 1.08 0.34-3.59 12.36 13.03 0.75-34.00 2.73 3.21 0.19-6.71 2.06 2.6 0.43-6.46 0.38 0.41 0.16-0.77 1.31 1.37 0.51-2.54

DOC 2.35 2.18 0.55-3.87 2.46 2.29 0.69-4.47 2.84 3.02 1.41-4.99 2.74 3.49 1.61-8.90 6.68 8.12 1.92-16.86 4.36 4.21 1.66-9.15 3.73 4.78 1.62-10.12 2.22 2.25 2.01-2.66 2.53 2.56 2.34-2.77

Note: Sites R - NT1 were surveyed in 2002-2003; D and DN were surveys in 20062007; NT2 was surveyed in both periods EpCO2 as a pollution indicator in domestic wastewater impacted rivers The EpCO2 indicating trophic condition in river water has been widely acknowledged (Trinh et al., 2007; Neal et al., 1998b) and in large extent it can be named as a pollution indicator because in many cases the rivers are considered as polluted if their waters become heterotrophic. This consideration withstands if the EpCO2 patterns show high correlation with other pollution determinands.

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Table 2: Linear regressions of median values of EpCO2 with other determinands Constant Gradient r2 pH 0.25 386.31 222.65 -49.5630.35 Temp 0.19 -79.9375.89 3.782.79 Alkalinity 0.71 -3.996.49 0.1590.04 Ca 0.70 -68.2921.07 2.840.65 PO4 0.81 14.542.33 20.003.46 NH4 0.73 15.432.67 2.810.60 DOC 0.86 -9.525.55 8.041.44 Chlorophyll-a 0.95 1.542.12 1.620.17 EpCO2 v pH

40

30

DN NT2

EpCO2

NT2 D

20

N3 NT1 N2

10 7.2

7.3

R N1 7.4

7.5

30

DN D NT2

20

N3NT1 R N2 N1

100

150

200

pH

50

10

50

DN D NT2 N3 NT1 R N2 N1

0.0

0.5

350

400

DN D NT2 N3 NT1 RN2 N1 0

2

4

6

1.5

50

30

NT2

2.0

D

DN

N3 NT1 R N2 N1 0

5

10 15 20 25 30 35 40

DOC

12

14

TL

40

NT2

30

DN D

NT2 20 10

PO4

10

EpCO2 v Ca (mg/l)

NT2

20

8

NH4

TL

10 1.0

300

40

NT2 EpCO2

EpCO2

20

20

EpCO2 v DOC (mg-C/l) TL

30

30

10 250

NT2

Alkalinity

EpCO2 v PO4 (mg-P/l)

40

TL

40

NT2

10

7.6

50

TL

EpCO2

40

EpCO2

50

TL

EpCO2 v NH4 (mg-N/l)

EpCO2

50

EpCO2 v Alk. (mg-HCO3/l)

25

N3 RN1 N2

NT1

30

35

40

Ca

Fig. 2: Plot median values of EpCO2 with other determinands at different sites In the studied region, as expected, median values of EpCO2 are positively correlated with median concentrations of PO4, DOC (Table 2 and fig.2). It is easily understood that if nutrient and DOC levels rise between sites, EpCO2 levels rise correspondingly. Instream EpCO2 levels are related to (a) generation of CO2 by microbial respiration, which breaks down organic carbon in the bulk water and sediments, and respiration by photosynthesising organisms at night, (b) uptake of dissolved CO2 during the day by suspended phytoplankton and macrophytes (Trinh et al., 2007) and (c) loss or gain of CO2 to or from the atmosphere at the air-river water interface. The closest correlations are found between EpCO2 and DOC, NH4 and PO4. They are characteristic of domestic wastewater effluents and provide the major source for microbial activity in rivers.

94

Surprisingly, EpCO2 is also highly positively correlated with chlorophyll-a though a negative correlation was expected due to dissolved CO2 consumption by phytoplankton. The simple explanation is that the dominance process in the studied sites is biodegradation of organic matter that overwhelm the photosynthesis. In such eutrophic sites, the higher the nutrients and degradable organic matter is loaded, the stronger the suspended phytoplankton (cyanobacteria dominance) develops. It proves the impact of domestic wastewater is highly significant in the regional rivers. The plot of median values between EpCO2 and other determinands also indicates the complexity of water quality in the studied region which one can simply define into 3 zones depending on the pollution levels: the undisturbed zone (R, N1, N2), polluted zone (N3, TL, NT2, NT2), and downstream zones (D, DN). Based on this simplification, Principal Component Analysis (PCA) is employed to identify the correlation of EpCO2 with pollution factor at different pollution stages. The loadings of EpCO2 and other determinands in PCA diagrams at undisturbed and polluted zones are shown in fig. 3. The first PCA component for polluted zone can be identified as pollution factor since all pollution determinands (BOD and PO4) have high loadings on it. Loading of EpCO2 on this factor is high as well. On the contrary, the PCA analysis for undisturbed zone shows different scenario. Pollution factor is not clearly defined since EpCO2 and other pollution determinands have different loadings on two most important components. These statistical results imply that the EpCO2 application for pollution assessment to domestic wastewater impacted rivers is potential. Polluted zone

Undisturbed zone

Loading Plot of EpCO2, ..., BOD

Loading Plot of EpCO2, ..., BOD PO4

0.0

Second Component

Second Component

EpCO2

pH

0.75 0.50 BOD 0.25Alkalinity PO4 NO3 0.00 -0.25 -0.50

-0.1

pH

-0.2 -0.3 BOD

-0.4 NO3

-0.5 -0.6

Alkalinity

-0.7

EpCO2

-0.8 -0.5

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

-0.50

First Component

-0.25

0.00

0.25

0.50

0.75

First Component

Fig. 3: PCA analysis-Loading plot of EpCO2 and other determinands at two studied zones

Self-cleansing potential As seen from table 2 and fig. 2, there is a positive relationship between EpCO2 and Alkalinity, but no clear relationship between EpCO2 and pH. If river water were close to equilibrium with atmospheric CO2, strong relationships would be expected between alkalinity, EpCO2 and pH. However, the complex set of processes leading to generation or consumption of dissolved CO2 and the generation or removal of carbonic acid is sufficient to decouple the relationship between pH, alkalinity and EpCO2 (Jarvie et al., 1997; Neal et al., 1997a,b, 1998a,b). In addition to Alkalinity, there is rational relationship between EpCO2 and calcium. This relationship suggests the possibility of calcite saturation in water column. If calcite saturation occurs within the waters there is a potential for phosphate removal by co-precipitation. To examine this possibility the calcite saturation was estimated based on alkalinity, pH, calcium and temperature information and the thermodynamic method provided by Neal et al. (1998a). The results have shown that on average, the waters are about saturated with respect to calcite, but the saturation varies between about a tent and ten 95

times saturation: log10SICalcite averages -0.07 with a range of -1.03 to +1.01. Log10SICalcite exhibits a strong linear relationship with pH and this corresponds with a change in carbonate concentration as a function of pH, but with near constant calcium and alkalinity levels and it implies that there is no calcite equilibrium within the water column (c.f. Neal et al., 1998c). This lack of equilibrium would be expected for the waters studied here as high DOC and phosphate concentrations inhibit precipitation (Neal, 2001, 2002). In reality, the correlation indicates that Ca variation among studied sites is influenced by wastewater inflow; the same source controlling EpCO2 variation. In addition, PO4 does not decrease downstream so the removal of PO4 was very unlikely in studied region. Thus, the results indicate that phosphate self cleansing mechanisms are not important in the water column of the rivers examined in this study. EpCO2 as indicator of seasonal change Previous study in the small basin of the Nhue River showed an increase of heterotrophic activity during late spring and early summer (Trinh et al., 2007). However, this trend was not clear defined due to the non-linearity of the hydrodynamic system. In this study, the seasonal change of trophic condition is debated again for large basin of the Day River. Data exploited from previous study is also taken into account. The monthly median EpCO2 are calculated and shown in table 3. Table 3: Monthly median values of EpCO2 at 4 rivers River Red Nhue ToLich Day

Jan. 10.4 15.0 53.9 6.7

Feb. 2.7 10.0 25.5 73.9

Mar. 4.0 9.9 42.0 25.2

Apr. 4.8 11.0 48.8 88.4

May 10.5 33.9 47.2 18.5

Jun. 14.4 36.8 25.3 61.9

Jul. 20.9 8.2 15.6 15.3

Aug 21.7 33.9 24.5 42.0

Sep. 78.2 88.5 22.5 17.5

Oct. 4.9 5.3 46.8 57.4

Nov 14.1 13.0 59.6 37.1

Dec. 15.2 47.7 96.2 16.7

Note: Surveys in the Day River taken in 2006-2007; in other rivers, surveys taken in 2002-2003 There are large variations in EpCO2 through out the year, although median values of EpCO2 are often high for individual rivers during the late spring to summer periods (table 3). Different from temperate region where the spring to autumn period represents the time of maximum primary production and thus maximum photosynthetic uptake of CO2 from the river water (Neal et al., 1998b), this highly biodegradable organic matter contained water region tends to produce more CO2 in summer time. It is explained that the region is located in tropical area where nutrients and radiation are available to support primary production throughout the year. The late spring and early summer are period of high temperature and low precipitation that increase the biodegradation of organic matter and cause high dissolved CO2. Besides, the precipitation and human controlled flow discharge are main factors affecting the fluctuating variation of EpCO2 in the regional rivers. CONCLUSION The results clearly indicate a series of river basins where EpCO2 levels are strongly influenced by untreated domestic wastewater inflow represented by high correlations with PO4, NH4, and especially DOC (table 2). For the whole region, due to the eminent impact of Hanoi metropolitan, the waters are often saturated with respect to atmospheric equilibrium. The EpCO2 level reaches as high as 2 orders of magnitudes. 96

Despite the simplicity of the features at the broad scale, detailed investigations for the individual zones show a complex pattern. For example, data scatter is high and there is poor correlation between EpCO2 and other water quality determinands. There is a tendency for higher values through the later spring to summer months as strong biodegradation. It is evident that the abundance of DOC prevented calcite precipitation within the water column though log10SICalcite were sometimes above the saturation level, leading to no self cleansing process in the system. Therefore, the measurement of EpCO2 using pH and alkalinity analysis needs to be considered an integral part of riverine environmental water quality and biological studies. REFERENCES Hartley, A.M., House, W.A., Leadbeater, B.S.C. and Callow, M.E. 1996. The use of micro-electrodes to study the precipitation of calcite upon algal biofilms. J. Colloid Interface Sci. 183: 498-505. Hope, D., Billett, M.F. and Cresser, M.S. 1994. A review of the export of carbon dioxide in river water, fluxes and processes. Environ. Pollut. 84: 301-324. House, W.A. 1989. Kinetics of crystallisation of solids from aqueous solutions. In: Comprehensive chemical kinetics reactions at the liquid-solid interface. vol. 28, chapter 3.Elsevier, Amsterdam. House, W.A., Denison, F.H. 1997. Transport of nutrients in a lowland river; Great Ouse, England, UK. Sci. Tot. Environ. 205: 25-49. House, W.A., Shelley, N. and Fox, A.M. 1989. Chemical modelling applications to experimental recirculating streams. Hydrobiologia 178: 93-112. Howard, J.R. 1984. Some Field and Laboratory Investigations of the Transfer of CO2 Across the Air-water Interface. Ph.D. thesis, The University of Liverpool. Jarvie, H.P., Neal, C., Leach, D.V., Ryland, G.P., House, W.A. and Robson, A.J. 1997. Major ion concentrations and the inorganic carbon chemistry of the Humber rivers. Sci. Tot. Environ. 194/195: 285-302. Kempe, S. 1982. Long term records of CO2 pressure fluctuations in fresh waters. In: Degens, E.T. (Ed.), Transport of carbon and minerals in major world rivers, part 1. MITT. Geol. Palaont. Inst. Univ. Hamburg, SCOPE/UNEP (Sonderbd), vol. 52, 91-332. Maberly, S.C. 1996. Diel, episodic and seasonal changes in pH and concentrations of inorganic carbon in a productive lake. Freshwater Biol. 35: 579-595. Neal, C. 2001. The potential for phosphorus pollution remediation by calcite precipitation in UK freshwaters. Hydrol. Earth Syst. Sci. 5(1): 49-58. Neal, C. 2002. Calcite saturation in eastern UK rivers. Sci. Tot. Environ. 282/283: 311-326. Neal, C., Harrow, M.L. and Williams, R.J. 1998c. Dissolved carbon dioxide and oxygen in the River Thames: Spring-summer 1997. Sci. Tot. Environ. 210/211: 205–218. Neal, C., House, W.A., Jarvie, H.P. and Eatherall, A. 1998b. The significance of dissolved carbon dioxide in major lowland rivers entering the North Sea. Sci. Tot. Environ. 210/211: 187-203. Neal, C., House, W.A. and Down, K. 1998a. An assessment of excess carbon dioxide partial pressures in natural waters based on pH and alkalinity measurements. Sci. Tot. Environ. 210/211: 173-185

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Neal, C., House, W.A., Jarvie, H.P., Leeks, G.J.L. and Marker, A.H. 1997b. Conclusions to the special volume of Science of the Total Environment concerning UK fluxes to the North Sea, Land Ocean Interaction Study: river basins research, the first two years. Sci. Tot. Environ. 194/195: 467-478. Neal, C., Robson, A.J. and Harrow, M. 1997a. Major, minor, trace element and suspended sediment variations in the River Tweed: results from the LOIS core monitoring programme. Sci. Tot. Environ. 194/195: 193-206. Quynh, L.T.P., Billen, G., Garnier, J., Thiery, S., Fezard, C. and Minh, C.V. 2005. Nutrient (N, P) budgets for the Red River basin (Vietnam and China). Glob. Biogeochem. Cyc. 19, GB2022. Trinh, A.D., Bonnet, M.P., Vachaud, G., Chau, V.M., Prieur, N., Vu, D.L. and Le, L.A. 2006. Biochemical modelling of the Nhue River (Hanoi, Vietnam); practical identifiability analysis and parameters estimation. Ecol. Mod. 193(3-4): 182-204. Trinh, A.D., Bonnet, M.P., Vachaud, G., Prieur, N., Vu, D. L. and Le, L.A. 2007. Experimental investigation and modelling approach of the impact of urban wastewater on a tropical river; a case study of the Nhue River, Hanoi, Vietnam. J. Hydrol. 334: 347–358.

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INFLUENCE OF SURFACTANT TYPES ON THE CORRELATION OF RETENTION FACTOR AND HYDROPHOBICITY OF TRIAZOLE FUNGICIDES USING MICELLAR ELECTROKINETIC CHROMATOGRAPHY Wan Aini Wan Ibrahim1, Dadan Hermawan, Mohamed Noor Hasan and Mohd Marsin Sanagi Separation Science Research Group (SSRG) Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia Corresponding author email address: [email protected]

ABSTRACT Application of micellar electrokinetic chromatography (MEKC) in quantitative structure-retention relationship (QSRR) has been studied for selected triazole fungicides. Effect of different surfactant types and concentrations of bile salts and sodium dodecyl sulfate on the correlation between logarithm of retention factor (log k’) in MEKC and logarithm of octanol-water partition coefficient (log Pow) was investigated. Five standard fungicides (cyproconazole, bromuconazole, epoxiconazole, bitertanol and difenoconazole) with known log Pow values from 2.9 to 4.3 were used for constructing the calibration curve of log Pow against the MEKC retention factor, log k’. High correlations were observed between hydrophobicity (log Pow) and log k’ in MEKC using two bile salt surfactants viz. sodium cholate and sodium deoxycholate and mixed bile salt systems, with squared correlation coefficient of linear regression greater than 0.98, due to the similar hydrogen bonding interaction patterns between bile salts MEKC systems and the octanol-water system. Keywords: Surfactans, micellar electrokinetic chromatography, retention factor, hydrophobicity, triazole fungicides, quantitative structure-retention relationship. INTRODUCTION The hydrophobic character of organic molecules can be used to predict biomembrane transport, bioaccumulation in plants and animals, and soil adsorption. Solute hydrophobicity is usually expressed by the thermodynamic octanol-water partition coefficient (Pow). The octanol-water partition coefficient is one of the most commonly reported physicochemical properties of drugs and industrial chemicals and the most widely employed descriptor for quantitaive structure-activity relationships (QSARs) for all kinds of biological, pharmaceutical and environmental property estimates (Poole et al., 2003). Determination of log Pow of compounds was developed by direct and indirect methods. Traditionally, the shake-flask method combined with UV assay was used for direct measurement of log Pow values (Danielsson and Zhang, 1996). This conventional method has some disadvantages: long analysis time (1 day/solute), interference from solute/solvent impurities and difficulty in 99

temperature control. Reversed-phase high-performance liquid chromatography (RPHPLC) (Donovan and Pescatore, 2002) and micellar electrokinetic chromatography (MEKC) for indirect log Pow determination (Garcia et al., 1996) were used by using the linear relationship between log Pow and log retention factor, log k’ (Equation 1). This equation is an example of quantitative structure-retention relationships (QSRR) (Jia et al., 2003; Woloszyn and Jurs, 1992). log Pow = a log k’ + b

(1)

where a and b are constants that can be determined from the observed data. While retention factor, k’, can be calculated from the experimental data. The advantages of these methods over the shake-flask method are rapid analysis, automation, temperature control, smaller sample requirements, and simultaneous separation of solutes. Micellar electrokinetic chromatography (MEKC) is a mode of capillary electrophoresis technique which was first introduced in 1984 by Terabe and coworkers. In MEKC, an ionic surfactant (micelle) is usually used as a pseudostationary phase that corresponds to the stationary phase in conventional chromatography and the surrounding aqueous phase to the mobile phase. The separation principle of analytes is based on their differential partitioning between micellar phase and aqueous phase (Quirino and Terabe, 1999). The migration order for neutral analytes in MEKC generally relates to the hydrophobicity of the analyte and retention behavior of analytes depend strongly on the type of surfactant/micelle (Nishi and Terabe, 1996). The correlation of MEKC retention factor (log k’) to octanol-water partition coefficient (log Pow) was found to be high (r2 = 0.835) for over 100 solutes with widely varying functionality (Herbert and Dorsey, 1995). This method reduces the laboratory-to-laboratory variability and the long analysis time due to the multiple mobile phase necessary in current HPLC methods for estimating log Pow. It was also reported that bile salts micellar systems provide better correlation for log k’ vs log Pow than SDS micellar systems (Yang et al., 1996). In this paper, MEKC with different type of surfactants (bile salts and sodium dodecyl sulfate) and concentrations will be investigated on the correlation between retention factor (log k’) in MEKC and hydrophobicity (log Pow) of standard triazole fungicides (Figure 1). To the best of our knowledge, there is no MEKC study being reported on the log Pow – log k correlation for the selected triazole fungicides. EXPERIMENTAL Chemical and reagents All triazole fungicides were obtained from Riedel-de Haen (Seelze, Germany). Sodium dodecyl sulfate (SDS) was obtained from Fisher Scientific (Loughborough, UK), sodium cholate from Anatrace (Ohio, USA), sodium deoxycholate from TCI Kasei (Tokyo, Japan), and borate buffer solution from Agilent (Germany). All other chemicals and solvents were common brands of analytical-reagent grade or better, and were used as received. Water was collected from a Millipore Water Purification System (Molsheim, France). The stock solutions of the individual triazole fungicides were prepared in methanol in the concentration range 2000 and 6000 ppm. Final dilutions (concentrations in the figures) were prepared by diluting the stock solution 100

with methanol. The separation solutions were prepared by dissolving appropriate amounts of surfactants in borate buffer solution. All running buffers were filtered through a 0.45 μm nylon syringe filter from Whatman (Clifton, USA). Apparatus and methods The MEKC experiments were performed on an Agilent capillary electrophoresis system with a diode array UV-Vis detector. The uncoated fused-silica capillary (Polymicro Technologies, Phoenix, AZ, USA) of 64.5 cm total length and 56 to the detector (75 µm I.D. × 360 µm O.D.) was used and thermostated at 25◦C. Injections were made at 50 mbar for 1 s. A Voltage of +25 kV was applied for the CE separation. Prior to the first run, the capillary was flushed with 0.1 M NaOH 20 min, water for 10 min, and micellar system for 10 min. Between run, capillary was rinsed with 0.1 M NaOH, water, and micellar system for 2 min each. The retention factor, k’, was calculated from the MEKC migration time according to the equation 2 (Terabe et al., 1984): k’ = [tR – tEOF]/ tEOF[1-(tR/tmc)]

(2)

where tR , tEOF , and tmc are the migration times (min) of the solute, the EOF marker (methanol), and the micelle marker (phenantrene), respectively. The technique is performed by analyzing a set of standards of known log Pow under the given MEKC conditions. Log k’ of each standard obtained is plotted against its log Pow to form a linear calibration graph. When a standard gives two peaks (as isomer/enantiomer), log k’ is calculated from the last peak. Table 1. Log Pow data of selected triazole fungicide standards No 1 2 3 4 5

Standard compound Cyproconazole Bromuconazole Epoxiconazole Bitertanol Difenoconazole

log Pow (literature)a 2.90 3.24 3.44 4.16 4.30

log Pow (prediction)b 2.92 3.18 3.43 4.10 4.38

Δ log Pow 0.02 0.06 0.01 0.06 0.08

a

Experimental log Pow data from literature (sourch: http://www.syrres.com/esc) Calculated log Pow data from DRAGON software (Dragon Professional version 5.42006, TALETE srl) b

RESULTS AND DISCUSSION The five standard triazole fungicides (Figure 1) have been selected to investigate the effect of surfactant types (sodium dodecyl sulfate and bile salts) and its concentrations on the correlation between log k’ in MEKC and log Pow. The literature log Pow value and the calculated log Pow value from DRAGON software of five standard triazole fungicides are shown in Table 1. The difference between literature and calculated log Pow value from DRAGON software was found to be ≤ 0.08.

101

N

N

N

OH N

Br

N N

O

O Cl

Cl

Bitertanol

Bromuconazole Cl

N

O

HO O

N

Cl

N

N N N Cl

Cyproconazole

O

Difenoconazol F

N

N O N

Cl

Epoxyconazole

Figure 1. Structures of selected triazole fungicides Sodium dodecyl sulfate (SDS) was first evaluated in the range of 30-50 mM in 4 mM borate buffer at pH 9.3. Separation of five standards of triazole fungicides was not successfully by MEKC with SDS, as illustrated in Figure 2. It can be observed that only two fungicides can be separated (cyproconazole and bromuconazole). Three other fungicides (more hydrophobic fungicides) were co-eluted with the micelle marker. This is due to the more hydrophobic fungicides interact more strongly with the SDS micelle. SDS is a long-alkyl-chain surfactant. This surfactant is believed to form spherical micelle having ionic group on the surface and the hydrophobic core. When ionic interactions are strong in MEKC with SDS, analytes will migrate at around tmc. Since the resolution was very poor, thus, effect of SDS as surfactant was not explored for further study on the correlation of log k’ and log Pow of these fungicides. The effect of bile salts (sodium cholate (SC), sodium deoxycholate (SDC), and mixed SC-SDC) as surfactants was then investigated. Bile salts are anionic surfactants found in biological sources. They have steroidal structures and form helical micelles having a reversed micelle conformation. Compared with SDS, bile salts have a relatively weak solubilization power. Figures 3-5 show the typical electropherograms of five triazole fungicides as a function of SC, SDC and mixed SC-SDC concentrations, respectively. Resolution was obtained for all five fungicides by

102

MEKC with bile salt as surfactant in concentration range of 30-50 mM. All five fungicides are chiral compounds with two chiral centers and bile salts are chiral surfactants. For cyproconazole and bromuconazole, two isomer peaks were observed in all concentration of bile salt system, except at 30 mM SC. While for three other fungicides, only one peak was observed in all conditions. Log k’ is calculated from the last peak of cyproconazole and bromuconazole isomers. Correlation coefficient of linear regression between hydrophobicity and retention factor in MEKC is illustrated in Table 2. High correlations were observed with correlation coefficient greater than 0.98 for all bile salt systems, due to the similar hydrogen bonding interaction patterns between bile salts MEKC systems and the octanol-water system (Yang et al., 1996). The best correlation coefficient was obtained at 40 mM SDC system as surfactant (r2 = 0.9912). Table 3 shows the log k’ values obtained in MEKC with 40 mM SDC for 5 triazole fungicides and the straight line equation between log Pow and log k’. The average of the relative errors from the straight line equation (Table 3) between literature and calculated log Pow values for all compounds was 2.80%. The results obtained in this work on the log Pow - log k’ correlation agree with those obtained by other authors who have found a good linear correlation log Pow - log k’ in MEKC for different compounds and various MEKC micellar systems (Garcia et al., 1996; Herbert and Dorsey, 1995). Table 2. Correlation coefficient (r2) of linear regression between hydrophobicity (log Pow) and retention factor (log k’) in MEKC with bile salts as surfactant Surfactant

30 mM

40 mM

50 mM

SC

0.9827

0.9865

0.9881

SDC

0.9909

0.9912

0.9898

SC+SDC (1:1)

0.9843

0.9879

0.9892

Table 3. Log k’ value of each triazole fungicides in MEKC system with 40 mM SDC and the equation of the straight line (log Pow vs log k’)

No

Standard compound

log k’

log Pow (literature)

1 2 3 4

Cyproconazole Bromuconazole Epoxiconazole Bitertanol

0.31 0.63 0.79 1.31

2.90 3.24 3.44 4.16

5

Difenoconazole

1.56

4.30

103

Equation log Pow = 1.1832 log k + 2.5195 r2 = 0.9912

(3+4+5+ 30 mM 2 1

EO

(3+4+5+ 40 mM 2 1

EO

(3+4+5+ 50 mM EO

2 1

Figure 2. Electropherograms of triazole fungicides with different SDS concentration. Sample, 100 ppm mixed standards (in methanol), injected hydrodynamically (HDI) for 1 s at 50 mbar (HDI); Separation solution: 30 - 50 mM SDS in 4 mM borate buffer (pH 9.3); capillary, 75 m I.D. x 64.5 cm (effective length, 56 cm); applied

104

voltage, +25 kV; detection wavelength, 200 nm; temperature, 20◦C. Peaks identification: 1 (cyproconazole), 2 (bromuconazole), 3 (epoxiconazole), 4 (bitertanol), 5 (difenoconazole), and 6 (micelle marker). CONCLUSION High correlations were observed between hydrophobicity (log Pow) and retention factor (log k’) in MEKC using two bile salt surfactants viz. sodium cholate and sodium deoxycholate and mixed bile salt systems. The best correlation coefficient of linear regression (r2 = 0.9912) was obtained by MEKC with 40 mM SDC in 4 mM borate buffer (pH 9.30). Log Pow estimation of test triazole fungicides by the best MEKC system will be evaluated in the further study. ACKNOWLEDGEMENTS The authors would like to thank The Ministry of Higher Education Malaysia, for financial support through the Fundamental Research Grant Scheme (FRGS), vote number 78074, and studentship for D. Hermawan.

105

2 30 4 1

5

3

6

2 40 1

4

1b

5

3

6

2 50 1 1b

4 3

5 6

Figure 3. Electropherograms of triazole fungicides with different SC concentration. Analysis condition as in Figure 2; Peaks identification: 1a, 1b (cyproconazole isomers); 2a, 2b (bromuconazole isomers); 3 (epoxiconazole); 4 (bitertanol); 5 (difenoconazole); and 6 (micelle marker).

106

2b

30 mM

4 5 6 1a

1b

3

2a

2b 40 mM 4 5 6 1a

1b

3

2a

2b

50 mM

4 5 1a

1b

6

3 2a

Figure 4. s of triazole fungicides with different SDC concentration. Analysis condition and peaks identification as in Figure 3.

107

30 mM

2b 4

5 6

3

1a 1b2a

2b 40 mM 44 55 6 6 1a

1b

3 3

2a

2b

50 mM

4 1a

5

1b 2a

3

6

Figure 5. Electropherograms of triazole fungicides with different mixed SDC-SC concentration. Analysis condition and peaks identification as in Figure 3.

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REFERENCES 1. Danielsson, L.G., Zhang, Y.H., 1996, Methods for Determining n-Octanol-Water Partition Constants; Trends Anal. Chem.; 15, 188-196. 2. Donovan, S.F., Pescatore, M.C., 2002, Method for Measuring the Logaritm of Octanol-Water Partition Coefficient by Using Short Octadecyl-Poly(Vinyl Alcohol) High-Performance Liquid Chromatography Columns; J. Chromatogr. A.; 952, 47-61. 3. Garcia, M.A., Diez-Masa, J.C., Marina, M.L., 1996; Correlation Between the Logarithm of Capacity Factors for Aromatic Compounds in Micellar Electrokinetic Chromatography and Their Octanol-Water Partition Coefficients; J. Chromatogr. A.; 742, 251-256. 4. Herbert, B.J., Dorsey, J.G.., 1995; n-Octanol-Water Partition Coefficient Estimation by Micellar Electrokinetic Capillary Chromatography; Anal. Chem.; 67, 744-749. 5. Jia, Z., Mei, L., Lin, F., Huang, S., Killion, R.B., 2003; Screening of OctanolWater Partition Coefficients for Pharmaceuticals by Pressure-Assisted Microemulsion Electrokinetic Chromatography; J. Chromatogr. A.; 1007, 203208. 6. Nishi, H., Terabe, S., 1996; Micellar Electrokinetic Chromatography Perspectives in Drug Analysis; J. Chromatogr. A.; 735, 3-27. 7. Poole, S.K., Patel, S., Dehring, K., Workman H., Dong, J., 2003; Estimation of Octanol-Water Partition Coefficient for Neutral and Weakly Acidic Compounds by Microemulsion Electrokinetic Chromatography using Dynamically Coated Capillary Columns; J. Chromatogr. B.; 793, 265-274. 8. Quirino, J.P., Terabe, S., 1999; Electrokinetic Chromatography; J. Chromatogr. A.; 856, 465-482. 9. Terabe, S., Otsuka, K., Ichikawa, K., Tsuchiya, A., Ando, T., 1984; Electrokinetic Separations with Micellar Solutions and Open-Tubular Capillaries; Anal. Chem.; 56, 111-113. 10. Woloszyn, T.F., Jurs, P.C., 1992; Quantitative Structure-Retention Relationship Studies of Sulfur Vesicants; Anal. Chem.; 64, 3059-3063. 11. Yang, S., Bumgarner, J.G., Kruk, L.F.R., Khaledi, M.G.., 1996; Quantitative Structure-Activity Relationships Studies with Micellar Electrokinetic Chromatography Influence of Surfactant Type and Mixed Micelles on Estimation of Hydrophobicity and Bioavailability; J. Chromatogr. A.; 721, 323-335.

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DETOXICIFICATION ABILITY OF JAPANESE FUNGI HIRATAKE AND BUNASHIMEJI FOR EXPLOSIVE CONTAMINATED LAND Do Ngoc Khue1, Phan Son Duong1, Pham Kien Cuong1, Trinh Xuan Gian1, Do Binh Minh1, To Van Thiep1, Morinaga T.2 1. Vietnam Institute of Science and Technology 2. Hiroshima Prefectural University (Japan) Introduction Recently, in many countries, biological resolutions are developed and effectively implemented to resolve land and water pollution 1. Amongst hose mentioned, using microorganism is widely used in pasteurizing daily used, hospital, food industrial, castle raising and planting sewage. However, the fact is that many industrial waste, such as those from textile, coloring, explosioning manufacturing, plant protection chemical (normally are perfumed organic, nitro compound, clo- ogranic or explosion) are waste that is difficult to resolve by microorganism. To these kinds of wastes, using white mushroom is normally bringing a better result 2-6. The reason is that because some of the white mushroom can create coaching enzyme such as Lignin peroxydase (LiP), Mangan peroxydase (MnP) and Laccase (Phenol oxydase). That are main enzyme taking part in the disintegrating polluted organics, and active level of this enzyme in mushroom or dust used to plant mushroom has an important effect to the resolution of that pollutants. Therefore, by determining active level of those enzyme in the mushroom or dust used to plant them, we can assess the possibility to use them for the purpose of pasteurizing environmental pollution 5. This article will introduce result of the study that determine active level of enzyme system in disintegrating lignin in dust sample that have been planted two kinds of Japanese mushroom, that are Hiratake (Pleurotus Ostreatus), marked as C1, C3, C4 and Bunashimeji (Hipsigus Marmoreus), and use dust to plant mushroom to pasteurizing land that effected with TNT explosion. Experimental Equipments To analyse active level of enzyme, Chemical- biological specializing equipments from the Laboratory of Chemical- biological- Institute of BiologicalChemical Food Technology- Hanoi University of Technology, have been used in which, there is the centrifugal UNIVERSAL: 32R-HETTICH (UK), light absorption spectrometer GENESX 20 (US). To determine the TNT content in all samples and determine the effectiveness of TNT detoxification process, the HPLC Model HP1100 (US) have been used. Chemicals Testing specializing chemicals to analyse active level of enzyme, disintegrating lignin, mentioned in documents 7-11 such as phosphate buffer 25mM, pH6,8; liquid L-DOP 10mM , phosphate 0,1M, pH6,5; Nalactat 0,25M; Bovine albumin 0,5%; MnSO4 2mM; H2O2 2mM; Red phenol; NaOH 2M have been used.

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Study objective Mushrooms and dust to plant mushroom Study objectives are 2 kinds of Japanese mushroom, that are Hiratake (Pleurotus Ostreatus) marked C1, C3, C4 and Bunashimeji (Hipsigus Marmoreus) marked as (SH), planted on teo shells with main elements: small grinding corn lid, (SH1) or sawdust (SH2). Samples are taken to analyse at different time when the mushroom have grown in full. Enzyme disintegrating lignin Enzyme studied in his case are: polyphenol peroxydase (marked as PP), Tyrozinase (marked as T), Laccase (oxygen oxidoreductase) (marked as L) and Mangan peroxydase (marked as MnP). TNT effected land sample TNT effected land sample has been taken from the area that land is effected by TNT of explosioning manufacturing site. Study methods Enzyme extracting method: scale up 5g of the dust sample used to plant mushroom in purified liquid, at 300C within 15'. Afterward, level it up to 40ml, centrifugal 10000 round/minute within 5', take the enzyme juice using to determine active level of enzyme. Method to determine active level of enzyme Active level of enzyme PP, T, L and MnP in the sawdust sample using to plant mushroom is determined as in document 7-10. It is worthing to note that active level of enzyme PP. PP is determined base on the tannic acid oxidation ability of the enzyme juice that creates brown product, presetable on the rock crystal plate as a brown circle surrounding the rock crystal whole. PP active is measured by mm is signaling between diameter of the delimit (D) with diameter of the rock crystal whole (d). Method to prepare testing sample Take 100- 200g of the TNT contaminated land (at level 85,6mgTNT/kg) that has been well grind, put into glazaed terra cotta of cynlinde shape with 20cm height, 15cm diameter, put 10- 20g well grind sawdust and then mix well. The humidity of the contaminated land should be maintaining at 65- 70%. Afterwart, take sample timely to analyse the TNT content remaining in the sample and determine the effecticeness of it. Method to determine the TNT TNT content in the contaminated sample can be determied by HPLC, as regulated in documetns 11. Results and discusison Result of the analysis the active level of enzyme system disintergating lignin in sawdust samples using to plant mushroom shows that active level of enzyme is effected by many factors in which, there are factors such as the monment taking enzyme jiuce, feature and elements of martirial used to create fungus… Some result is about the change according to time of the enzyme active level that disintergate lignin

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in the sample of dust used to plant fungus Hiratake (Pleurotus Ostreatus) (kind C4), mentioned in table 1. From the result in table 1, we can see that there is different in transforming principles of the studied enzyme active level . For example, active level of enzyme Polyphenol peroxydase is not much changed inall duration of 100 days of experiment, while those of Tyrozinase has increased thousnd time after 100 days planted. With 2 reamaining enzyme (Laccase & MnP), they have highvalue at the time of taking sample- day 4070 after planting, however, the only change in MnP is noticable. On the first 30 days or after 90 days, the active level of MnP in all samples is Zero.

Table 1: Impact of sample taking time, since mushroom is planted to the active level of enzyme and the effectiveness of disintergating TNT in contaminated land (H %) of the sawdust fungus planting Hiratake (C4) Time taking sample, on day enzyme active 30 40 60 77 86 107 level PP (D-d)(mm) 4 6 4 4 4 3 Tyrozinase, 4,4.10-5 7,22.10-5 2,78.10-4 7,11.10-2 14,2.10-2 12,67.10-2 (U/g) Laccase, (U/g) 13072 19040 20960 17104 15456 13856 MnP, (U/g).10-3 0 8,77 16,33 3,613 0,72 0 H(%) 28,90 89,66 96,42 93,38 84,38 57,80 Note:

- PP: Polyphenol peroxydase - H: the output of pasteurizing TNT in the contaminated land

This is a fact need to be concern, as Laccase and MnP are two main important enzyme that plays important role in the disintegrating reaction to lignin compound, perfumed containing compound...5. Therefore, selecting dust sample to plant mushroom at the right time that Laccase & MnP active level is high is very important to implementing effectively the pollution resolution process by planting mushroom. Base on determining the TNT content left in the dust sample after 15 days of experiment has already determine the output of disposing TNT (%) by dust for planting Japanese Hiratake (kind C4). result notes in table 1 shows that the above conclusion is solid. Any dust sample with Laccase & MnP high active level, the output of TNT resolution is also high. From the result in table 1, it can be noted that different from the case that Laccase and MnP have not found to be effected from the two enzyme, that is Polyphenol peroxydase & Tyrozinase to the disposing of TNT. this shows that only fungus that create lots of enzyme Laccase and MnP are able to produce the output for the perfumed or nitro compound cleaning, of which, there is TNT The result of determining enzyme that disintegrating lignin in some dust samples used to plant eatable mushroom and popular medicine in Vietnam are listed in table 2. Table 2. Active level of enzyme system that disintegrating lignin and the TNT pasteurizing output 112

Kind of No mushroom

1

C1

2

C3

3

SH2

Source

Japanese Japanese

4

SH2

5

SH2

6

SH1

7

SH1

8

SH1

Japanese

Japanese

Japanese

Japanese

Japanese

Japanese

Main enzyme active level time TNT material Development taking pasteurizing to make status of MnP, output after sample, PP, shell to L, mushroom T, u/g u/g date 15 days, % plan mm u/g -3 10 mushroom Corn lid

Harvested

210

3

Corn lid

Harvested

210

2

Sawdust

Fully Grown

36

2

3,33.10-

3600

0

61,25

6480

0

74,76

140

1,8

43,2

302

1,5

35,1

130

0

22,3

3

242

2,1

46,1

2

6,0. 102

2,4. 103

5,7. 10-

Sawdust

Fully Grown

55

3

Sawdust

Fully Grown

77

1

Corn lid

Fully Grown

36

2

Corn lid

Fully Grown

53

3

6,67. 10-3

432

1,8

47,2

Corn lid

Fully Grown

77

1

2,67. 10-2

165

0,0

21,5

3

2,2. 102

3,8. 10-

From result in table 2, we see that the enzyme active level depends on kind of mushroom and dust used to plant mushroom, time that samples are taken. Dust used to plant Japanese Hiratake (C1, C3) is made from well grind corn lid normally produce higher level of enzyme Laccase active, compared to those nurtured by dust made from corn lid, or sawdust used to plant mushroom Bunashimeji (SH3/1). the active level of enzyme in the dust sample also depends on sample taking time. Foe example, with Bunashimeji (SH1- SH2), if taking sample on say 36 – 55, there are still MnP, however, if after day 77, this MnP is died out. In general, dust to plant mushroom Bunashimeji (SH1- SH2) has laccase and MnP active level more than 10 times lower than those used to plant Hiratake. This may be the main reason why the TNT killing output of the dust sample of this kind of mushroom is lower than those of Hiratake (Pleurotus Ostreatus) C1, C3 (table 2), C4 (table 1). From result in table 1, we see that by using dust to Hiratake (kind C4 (6/1) for example), we can effectively pasteurizing dirt effected by TNT (at the output level of 93,3% after 15 days of treatment, much higher than dust used to plant other kind of mushroom, especially to the Bunashimeji). It is necessary to note that dust used to plant this mushroom can be kept in a long time in a normal condition (up to 7

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months), the high active level of some enzyme disintegrating lignin such as Tirozinase, Laccase (sample 1, 2 table 2). This is a practical and meaningful feature of this kind of dust Conclusion From the above study, it can be concluded that: + There are enzyme disintegrating lignin in sample of dust using to plant some kind of Japanese mushroom: such as Hiratake (Pleurotus Ostreatus) and Bunashimeji (Hipsigus Marmoreus). + Active level of enzyme that able to disintegrating Lignin in samples of dust using to planting mushroom depend on the nature of mushroom type, dust used to plant is, the development level of mushroom as well as sample taking time. + Dust used to plant Japanese Hiratake from corn lid normally produce Higher enzyme active level (especially laccase), higher than those use to plant Bunashimeji. This may be the reason leading to the high output in TNT pasteurizing resolution, when compared it to other kind of dust used to plan other kind of mushroom. The study is completed thanks to the financial sponsor from the Fundamental research program for natural Science. References [1] Chandry G. R (1994). Biological Degradation and Bioremediation of toxic chemicals. Chapman and Hall. [2] Aust S. D (1993). The fungus among us: use of white rot fungi to biodegrade environmental pollutants. Environ. Heth Perspect, 101, 232 – 233. [3] Barr D. P. and Aust S. D (1994). Pollutant degradiation by white rot fungi. Rev. Environ. Contaijn and Toxicol, 138, 49 – 72. [4] Bumfus J. N, Tien M., Wright D and Aust S. D (1975) Oxidation of persistent environmental pollutants by a white rot fungus. Science, 228, 1434 – 1436. [5] Christipher Bucke (1998) Extended Summeries Biochemistry of Bioremediation by Fungi. J. Chem. Techal Biotechnol, 4, 356 – 367. [6]. Ikehata K., Buchanan I. D., Smith D. W. (2004). Recent developments in the production of extracellular fungal peroxidases for Waste treatment. J. Enviral:Eng. Sci., 3, 1 – 19. [7] Solaya Suksa-ard, Kasetsart University”plant a tree plant love [8] R.C. Minussi, S.G. de Moraes, G.M. Pastore and N. Duran (2001). Biodecolorization screening of synthetic dyes by four white-rot fungi in a solid medium: possible role of siderophores. Letters in Applied Microbiology , 33, 21±25 [9] http://www.sigmaaldrich.com/img/assets/18160/Laccase.pdf [10] Nonhyun-dong, Kangnam-Ku, seul, Korea, (2002). Application Note The measurement of tyrosinase activity using PDA UV-Vis Spectrophotomete. [Sinco.com/application_data_en/AB2009.pdf]. [11] Harvey S.D, Fellows R.J, Cataldo D.C, Bean R.M (1990) Analysis of 2,4,6trinitrotoluene and its transformantion products in soils and plant tissues by high performance liquid Chromatography. J. Chromatogr. 518, p. 361- 374.

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APPLYING LOW ULTRASONIC IN GRIGNARD REACTIONS FOR SYNTHESIS OF THE INSECTS’ PHEROMONES AND ATTRACTANTS Dang Chi Hien, Nguyen Cong Hao, Nguyen Cuu Thi Huong Giang, Le Thanh Son, Nguyen Thanh Danh Institute of Natural Products Chemistry in Ho Chi Minh City, Vietnam ABSTRACT Low power ultrasonic equipment was applied success for the synthesis of some insect attractants such as Ethyl 4-methyloctanoate, 4-methyl-5-nonanol, 6-metyl-2-hepten-4ol … in high yield. This technique requires only simpler of glassware and manual than mechanical stirring and large savings time when carried out in the Grignard reaction, the carbon coupling with organocuprate catalysis … Discovery in this technique opens up new prospects for applying ultrasonic to synthesize the high bioactivity compounds in the controlling harmful insects’ pest without pollution environment. Key words: Grignard reagents, a cleaner ultrasonic, processor ultrasonic, Rhynchophorus sp. weevil, Rhinoceros beetle. INTRODUCTION Grignard reaction was the most widely used organometallic reagents in organic synthesis. Grignard reagents, or organomagnesium halides (RMgX), were one of the most synthetically useful and versatile classes of reagents available to the organic chemist. Over the years, Grignard reaction has been used for synthesis a wide variety of insect pheromones and attractants. Conditions for these reactions are always very strictly (especially dry with equipments and anhydrous, non-epoxide with solvents). However, in this report a low ultrasonic system with combination between a cleaner ultrasonic (advantage in making of Grignard reagent period) and a processor ultrasonic (advantage for reaction period with low temperature) has been applied successful in Grignard reaction to synthesize some of insect attractants such as: Rhynchophorus sp. weevil, Rhinoceros beetle (Morin JP., 1994; Hallett R.H, 1995, Gries R., 1996), Conogethes sp. (Konno Y., 1982; Mori K., 1990), Prays citri (Nguyen Cong Hao, 2003)… in high yield. This technique required not only simpler of glassware and manual than mechanical stirring equipment but also a large savings time (the product is ready for assay in one or two hours). The solvents for reaction didn’t need also kinds of “anhydrous reagent solvents” and the Grignard reaction could work faultless in the rain storm days with the very humid air. Some of the Grignard reaction have used low power ultrasonic for the syntheses products such as: the alcohols synthesis group, the produces from coupling of RMgX and RX, the produces from coupling of RMgX and ROTs and the produces from rearrangement allyl. Discovery in this technique opens up new prospects for applying ultrasonic to synthesize the high bioactivity compounds in the controlling harmful insects’ pest without pollution environment.

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RESULTS AND DISCUSSION Instruments Ultrasonic cleaner POWER SONIC 405 and Ultrasonic processor HIELSCHER UP50H or Ultrasonic processor GE 130 were used in the syntheses of Grignard reactions.. Syntheses Scheme 1 BuMgBr/Et 2O

CHO

0oC

(1)

(2)

OH

BrMg

CHO Et2O, 0oC

(3)

CHO

C5H11MgBr o

OH (4)

C5H11

Et 2O, 0 C OH (16) (16') The Alcohols Syntheses Group Ferrugineol 4-methyl-5-nonanol, the aggregation pheromone of the Asian Rhynchophorus weevil (Rhynchophorus ferrugineus Oliv.) was synthesized from 2methylpentanal and butylmagnesium bromide, reaction time: 30 min at 0oC and 30 min. at room temp., yield: > 90%GC (monitoring). This biology synthesis compound was proved that its capable attraction very effective with Rhynchophorus weevil in the Mekong delta of Vietnam. Rhynchophorol 6-methyl-2-hepten-4-ol, the aggregation pheromone of the American palm weevil (Rhynchophorus palmarum) was synthesized from crotonaldehyde and isobutylmagnesium bromide, reaction time: 30 min at 0oC and 30 min. at room temp., yield: 97%GC, (monitoring). Synthon 1-octen-3-ol for the synthesis of (E)-10-hexadecenal, sex pheromone of the Yellow Peach Moth (Conogethes punctiferalis G.), was synthesized from acrolein and pentylmagnesium bromide, reaction time: 30 min at 0oC and 15 min. at room temp., yield: >95%GC (monitoring).. Grignard reagents are extremely strong bases that can react violently with hydroxylic compounds such as water or alcohols. The metal hydroxide (or alkoxide) formed in the above reaction by humid air is a white solid. We will be using a sonicator which will alleviate some of the problems with wet solvents and reagents. In the laboratory, initiation of the Grignard reaction is sometimes very slow. In the presence of air, a coating of magnesium oxide forms on the metal turnings. This coating must be removed or the reaction will not initiate. A ultrasonic cleaner removes the coating. This convenient method is used in the syntheses Organic Chemistry.

116

Scheme 2 EtMgBr/THF

OTs

Li2CuCl4, - 78oC

(5)

(6)

BuMgBr/THF

OTs

Li2CuCl4, - 78oC

(5)

(7)

The Produces from Coupling of RMgX and ROTs Synthon 2,6-dimethyl-2-decene from 3,7-dimethyl-6-octenyltosylate and ethylmagnesium bromide, reaction time: 30 min. at -78oC and 30 min. at room temp., catalyst: Li2CuCl4/THF (Corey E.J, 1985; Fouquet G., 1974), yield: 93.8%GC (monitoring). Synthon 2,6-dimethyl-2-dodecene from 3,7-dimethyl-6-octenyltosylate and butylmagnesium bromide, reaction time: 30 min. at -78oC and 30 min. at room temp., catalyst: Li2CuCl4/THF, yield: 92.5%GC (monitoring). Scheme 3 EtMgBr/THF

Br (15) O

BrMg (8)

+

O

Li2CuCl4, 0 - 5oC

THF

Br

Br

(6) O Br

Li2CuCl4, - 78oC

O

(9)

(10) MgBr

O

Br (11)

O

O Li2CuCl4, 0 - 5oC

(12)

O

The Produces from Coupling of RMgX and RX Synthon 2,6-dimethyl-2-decene has still synthesized from 3,7-dimethyl-6octenylbromide and ethylmagnesium bromide , reaction time: 15 min. at 5oC; 60 min. at 45 - 50OC, catalyst: Li2CuCl4/THF, yield: 96%GC (monitoring). Synthon 5-bromopentanal ethyleneglycol acetal for the synthesis of (E)-10hexadecenal and (Z)-7-tetradecenal (Nguyen Cong Hao, 2005), sex pheromone of the Yellow Peach Moth (Conogethes punctiferalis G.) and female sex pheromone of the Citrus Flower Moth (Prays citri), was synthesized from 3-bromomagnesium pentanal ethylenglycol acetal and 1,2-dibromo ethane, reaction time: 15 min. at -10oC; 60 min. at room temp., catalyst: Li2CuCl4/THF, yield: 97%GC. And ultrasonic processor appropriated with reaction period. The flask was attached to the ultrasonic probe, and the lower portion was immersed in the mixture reaction and soln. constant temperature bath maintained at low temp. The reaction mixture was sonicated for 5 min – 1 hrs in a 6-sec pulse mode. After sonicating, the flask was detached from the probe, and the reaction mixture was treated.

117

Scheme 4 C 5H11 BrMgC6H12OTHP H C 11 5 CuI, -10oC

C7H14OTHP

OAc (14) (13) The Produces from Rearrangement Allyl (E)-8-Tetradecen-1-yl tetrahydropyran-2-yl ether, a important medium synthon for the synthesis of (E)-8-tetradecenyl formate or (E)-10-hexadecenal, was synthesized from 6-bromomagnesium hex-2-yl tetrahydropyran-2-yl ether and 3-acetoxy-1-octene , reaction time: 60 min. at -10oC; 30 min. at room temp., catalyst: CuI/THF, yield: 88%GC.

Table 1: Comparing of the yield (%) of using between ultrasonic and mechanical stirring in the some of Grignard reactions. Ultrasonic Reagents Time Aldehydes or others (RX) (min) n-BuCl 30 - 60 2-metylpentanal n-BuBr 30 - 60 2-metylpentanal i-BuBr 30 - 60 crotonaldehyde EtBr 30 - 45 acrolein C5H11Br 45 acrolein EtBr 75 citronellyl bromide R1Br 60 solid CO2 (a) monitoring; R1Br: 1-Bromo-3-methylheptane. Reagents (RX) R2Br R3Br

Time (min) 75 75

Aldehydes or others

Pure(a) (%GC) 90.1 97.0 97.7 99.7 96.3 96.2 99.0

Yield (%) 89.5 94.1 95.2 90.0 93.5 85.3 80.1

Pure(b) (%GC) 97 98

Yield (%) 70 83

Pure (%GC) 80 85 88 89

Yield (%) 77.1 82.9 85.1 87.2

1,2-dibromoethane 3-bromopropanal ethyleneglycol acetal R4Br 90 3-acetoxy-1-octene 98 88 (b) After chromatography column; R2Br: 3-bromopropanal ethyleneglycol acetal; R3Br: 2-hexyl bromide; R4Br: 6-bromomagnesium hex-2-yl tetrahydropyran-2-yl ether. Mechanical stirring Reagents Time (RX) (hrs) n-BuCl 15 i-BuBr 15 n-BuBr 15 EtBr 15

Aldehydes or ketones 2-methylpentanal crotonaldehyde 2-butanone cyclohexanone

118

Table 2: Comparing of the yield (%) of using between ultrasonic and mechanical stirring to depend on the reaction time. (Substitute reaction of citronellyl tosylate(a) and Grignard reagents at -780C, Li2CuCl4 catalyst)

Reagents (RMgX) EtMgBr

BuMgBr Reagent (RMgX) EtMgBr

Ultrasonic Time (min) Pure (b)(%GC) 20 77.5 25 85.2 30 93.8 35 90.1 30 92.5(c) Mechanical stirring Time (hrs) Pure (b)(%GC) 15 87.4

Yield (%) 74.3 81.1 91.3 86.9 89.2 Yield (%) 83.5

(a)

Citronellyl tosylate was synthesized in the ultrasonic conditions:the mixturereaction including citronellol, TsCl/Py – CH3Cl; time 25 min.; temp -10oC; yield 94%GC (monitoring). (b)monitoring; (c)2,6-dimethyl-2-dodecen. The use of ultrasound has two distinct advantages over traditional mechanical stirring methods. The ultrasonic waves serve as a driving force which was independent of temperature, allowing reaction temperatures to be varied over any desired range. Secondly, the power of the ultrasonic driving force can be varied by using a variable power ultrasonic probe. Ultrasound in 20 kHz to 10 MHz range, preferably 20 kHz to 55 kHz, and having acoustic wavelengths in the range of from about 7.6 to about 0.015 cm may be employed in the practice. A standard of ultrasonic cleaner as 100 - 125 W, 45 - 60 kHz and an ultrasonic processor as 100 W, 60 KHz have been used. The water bath will heat up to about 35oC in about an hour of continuous sonicating. A sizable amount of ether evaporated during sonication and reaction (Smith D.H, 1999; Nathan A., 2003). Compounds Used for Grignard Reaction Reagent period: Almost alkyl bromides was created Grignard reagents very well. Of these reagents, only p-bromotoluene and completive substances of bromide (see Table 1) have been slow, but it started as well as the others. However, these bromide compounds need to be introductory reaction carefully. Alkyl chloride in sodium-dried ether can also happen reaction sooner with ultrasonication (see Table 1). However, the initiation time is greater than 30 minutes. Virtually all Grignard reagents were happened within five minutes; most start within 45 seconds. In contrast, without sonication, 1-bromobutane did not begin reacting with magnesium for at least two minutes. About 10 - 15% of the magnesium remains. Generally, time of reagent period was medium about 60 min. Reaction period: Using ultrasonic probe, aldehydes and some ketones work well, but their odor was unnecessarily strong. Yields of alcohol of medium 90% were observed (see Table 1). The product distribution via GC was identical to the nonsonicated reaction. Tosylate has been given high pure (> 90%GC, monitoring) of the products (see Table 2). The others need to purify on chromatography column after reaction period. Yields of those were about 70 – 88%. 119

The Limits of This Method Old magnesium turnings with a black surface and just a small amount of brighter metal were also tried. The reaction started in the same time as the reaction with better quality magnesium. 1-Bromobutane in methyl tert-butyl ether did not react using the ultrasonic method (Smith D.H, 1999). However, some of less flammable solvents (THF, …) can be substituted for diethyl ether as the solvent for the aldehydes, ketones or the others. Not dropping alkyl bromide too rapidly, these excess will be coupling with Grignard reagent portion before and will create the by-products without expectation. The use of the ultrasonicator will initiate Grignard reactions with organic bromides very rapidly with very little failure under conditions of laboratories. The ultrasonicator also allows the use of much less expensive grades of ether or soln., with no apparent penalty in product yield or quality. Benefits, characteristics and conditions to use an ultrasonic cleaner for Grignard reactions: o Preparative of Grignard reagents are always quickly (reagents are often ready for reaction in one hour). o Solvents for reagent can come from a half anhydrous. o Can heat flask to 50 - 60oC, appropriate for Grignard reagent period but can not be used at low temp. o With alkyl bromide, reagents were made up very rapidly with little failure. Benefits, characteristics and conditions to use an ultrasonic processor for Grignard reactions: o Coupling reactions happened not only rapidly but also a large saving time remarkably. o Advantage for reactions in low temp. and well mixture. o Can combination with microwave to increase effective of some reactions. CONCLUSION In the laboratory, the low power ultrasonic (20 – 100 KHz) has been proved that they can apply effective in the synthesis of some insects’ attractant compounds. Applying ultrasonic techniques in the Grignard reactions has been saved a large of time in high yields and can use soln. from a half anhydrous. Moreover, this technique required only simpler of glassware and manual than mechanical stirring equipment as well as it could work faultless in the rain storm days with the very humid air. It is true that its synthesis technique is a progressive of the Green Chemistry. All of above syntheses attractants have given effect to insects in the field trials. These open up prospect to apply bioactive compounds controlling with harmful insects’ without environment pollution. Experiments IR spectra were accomplished with apparatus IR BRUCKER EQUINOX 55. 1H NMR and 13C NMR spectra were recorded on apparatus BRUCKER AVANCE 500 NMR Spectrometer at 500 MHz and 75 MHz, at 300 MHz and 75 MHz on apparatus VARIANCE MERCURY 300 NMR Spectrometer or at 200 MHz and 75 MHz on apparatus BRUCKER AC 200 NMR Spectrometer Spectrometer. Gas Chromatography: Hewlett Packard 5890 – SERIES II. General Procedure for Syntheses Alcohols from Grignard Reactions using Ultrasonic: The Grignard reagent was created between alkyl bromide (60 mmol) and magnesium (1.44 g; 60 mmol) in ether (40 ml) soln and performed in the ultrasonic

120

bath. This solution was slowly added dropwise via cannula to a soln of aldehyde (30 mmol) in ether (40 ml) cooled at 0oC. After sonicating (using ultrasonic processor) for 30 min at 0oC and 30 min at room temperature (t.l.c monitoring), the mixture was poured into sat NH4Cl and extracted with ether. The organic layer was washed with sat NaHCO3 aq., water, brine and dried (MgSO4) (hereafter referred to as the “washing protocol”), concentrated in vacuo. The crude product was employed in the next steps after fractional distillation or through out chromatography column. Ferrugineol (±) 4-methyl-5-nonanol (2). The product as a colourless liquid (Yield: 94%), bp 980C/13 mmHg, IR (max, cm-1) 3371 (OH); 1H NMR (500 MHz, CDCl3, δ ppm) 0.85 – 0.92 (m, 9H, 3CH3), 1.06 – 1.51 (m, 11H, CH2 and CH-CH3 ), 3.43 (m, 1H, CH-OH), 3.49 (br m, 1H, OH); 13C NMR (CDCl3, δ ppm) 13.55 (C9), 14.10 (C1), 14.35 (C10), 20.49 (C2), 22.84 (C8), 28.51 (C7), 34.21 (C3), 35.66 (C6), 37.94 (C4), 75.34 (C5). Rhynchophorol (±) (E)-6-metyl-2-hepten-4-ol (4). The product as a colourless liquid (Yield: 95%). bp 36 – 37oC/3 mmHg; IR (max, cm-1) 3365 (OH) cm-1, 1674 (w, C = C), 965 (s, (E)-CH = CH); 1H NMR (200 MHz, CDCl3):  0,89 (d, J = 6.6 Hz, 6H, (CH3)2CH), 1.18 – 1.99 (m, 3H, H-5, H-6), 1.66 (d, J = 5.6 Hz, 3H, CH3C = C), 2.1 (br.s, 1H, OH), 4.05 (m, 1H, H-4), 5,44 – 5,64 (m, 2H, CH = CH); 13C NMR (CDCl3, ppm)  17.54 (C1), 22.79 (C6), 24.13 (C7), 24.42 (C8), 46.32 (C5), 71.18 (C4), 126.32 (C2), 134.63 (C3). 1-octen-3-ol (16’). The product as a colourless liquid (Yield: 93.5%) 1-octen-3-ol. bp174 – 175oC. d 0,837 g/cm3. IR(ν, cm-1): 3362 (br., O – H), 3082, 2929, 2861, 1845, 1644, 1461, 1425, 1315, 993 (m, C – O), 922. 1H NMR (CDCl3, ppm) δ 0,88 (t, J = 6.7 Hz, 3H, CH3); 1.26 – 1.43 (m, 7H, CH2 và OH); 1.47 – 1,52 (m, 2H, H-7); 3,64 (t, J = 6.7 Hz, 2H, CH2-O); 4,1 (m, 1H, CH); 5.09 – 5.23 (m, 2H, CH2=); 5.87 (m, 1H, CH=CH2). 13C NMR (CDCl3, δ ppm) δ 14.03 (C8); 22.62 (C7); 25.03 (C5); 31.79 (C6); 37.06 (C4); 73.3 (C3); 114.51 (C1); 141.4 (C2). General Procedure for using Ultrasonic and Catalyst in the Syntheses Compounds from Grignard Reactions: The Grignard reagent was created between alkyl bromide (75 mmol) and magnesium (1.8 g, 75 mmol) in THF (40 ml) soln and performed in the ultrasonic bath. This solution was slowly added dropwise via cannula to a soln of citronellyl tosylate (8.67 g, 28 mmol) in THF (40 ml) cooled at -78oC, which contained a catalytic amount of Li2CuCl4 0.1 M (15 ml). After sonicating (using ultrasonic processor) for 1hr (t.l.c monitoring) at - 78oC, the mixture was poured into sat NH4Cl and extracted with ether. The organic layer was washed protocol, concentrated in vacuo. The crude product was employed in the next steps after fractional distillation or through out chromatography column. (±) 2,6-dimethyl-2-decene (6). The product as a colourless liquid (91%), bp 510C/12 mmHg, IR (max, cm1): 2970, 2930, 2880, 1654 (w, C = C), 1460, 1380, 1128, 1079, 962 (m, C = C), 840. 1H NMR (300 MHz, CDCl3):  0.84 (d, J = 6.6 Hz, 3H, CH3-6), 0.88 (t, J = 6.6 Hz, 3H, H-10), 1.27 (m, 7H, CH and CH2), 1.6 (s, 3H, CH3-2), 1.68 (s, 3H, CH3-2), 1.9 (m, 2H, H-4), 5.07 (t, J = 5.7 Hz, 1H, H-3). 13C NMR (CDCl3, ppm)  14.18, 17.62, 19.63, 23.08, 25.62, 25.73, 29.33, 32.44, 36.70, 37.20, 125.13, 130.91. (±) 2,6-dimethyl-2-dodecene (7). The product as a colourless liquid (89%), bp 68oC/10 mmHg. IR (max, cm1): 1646 (w, C = C), 976 (m, C = C). 1H NMR (300 MHz, CDCl3):  0.84 (d, J = 6.6 Hz, 3H, CH3-6), 0.88 (t, J = 6.6 Hz, 3H, H-12), 1.06 - 1.44 (m, 11H, CH and CH2), 1.6 (3H, s, CH3-2), 1.68 (3H, s, CH3-2), 1,93 – 1,99 (m,

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2H, H-4), 5.08 – 5.13 (t, J = 6 Hz, 1H, H-3). 13C NMR (CDCl3, ppm)  14.34, 17.83, 19.84, 22.94, 25.83, 25.93, 27.24, 29.93, 32.30, 32.66, 37.23, 37.40, 125.36, 131.13. 2,6-dimethyl-2-decene (7) from citronellyl bromide: Sonicating (using ultrasonic processor) for 30 min (t.l.c monitoring) at 0 - 5oC and reflux condenser for 2 hrs . The product as a colourless liquid (85%). Spectra results of (7) were corresponding with (6). 5-bromopentanal ethylenglycol acetal (10). The molecular rate between Grignard reagent and the mixture reaction = 1 : 1; catalyst: Li2CuCl4 0.1 M , reaction time: 15 min. at -10oC; 60 min. at room temp., catalyst: Li2CuCl4/THF, the product as a colourless liquid. (Yield: 70%), bp 98-100oC/15mmHg; nD28 =1,4721. IR (max, cm1): 2935, 2860, 1460, 1410, 1370, 1140, 1035, 945, 730, 650. 1H NMR ( 200 MHz, CDCl3):  1,3-2,0 (m, 6H, CH2); 3,49 (t, J=6Hz, 3H, CH2Br); 4,77 (t, J = 4Hz, 1H, OCHO); 3,7-3,9 (m, 4H, OCH2CH2O). 4-methyloctanal ethyleneglycol acetal (12). The molecular rate between Grignard reagent and the mixture reaction = 1 : 1; catalyst: Li2CuCl4 0.1 M , reaction time: 15 min. at 5oC; 60 min. at room temp., catalyst: Li2CuCl4/THF, the product as a colourless liquid. (Yield: 83%), bp 650C/5 mmHg. 1H NMR (500 MHz, CDCl3): 0.89 (m, 6H, CH3-4 and H-8), 1.12 -1.34 (m, 6H, H-5,6,7), 1.42 (m, 2H, H-3), 1.67 (m, 1H, CH), 2.64 (m, 2H, H-2), 3.7 - 4.1 (m, 4H, OCH2CH2O), 4.95 (t, J = 5 Hz, 1H, H1). (E)-8-Tetradecen-1-yl tetrahydropyran-2-yl ete (14). The rearrangement reaction was performed by the coupling between Grignard reagent (from 6-bromohex-1-yl tetrahydropyran-2-yl ether (7.95 g, 30 mmol) and Mg (0.72 g, 30 mmol) in 40 ml THF) and 3-acetoxy-1-octene (13) (1.58 g, 10 mmol), along with amount of CuI (3.43g, 18 mmol) as a catalyst. After sonicating (using ultrasonic processor) for 1hr (t.l.c monitoring) at - 10oC and 30 min at room temperature, the mixture was poured into sat NH4Cl and extracted with ether. The organic layer was washed protocol, concentrated in vacuo. The residue gave the crude product 3.02g (91%). Chromatography silica gel column (50 g). The first fraction (petroleum ether : ether = 50 : 50) gave 2.65 g (88%). The pure product has been gotten from the separation again by silica gel 100 – 150 mesh (100g) and AgNO3 (20% the compound). The fraction of 10% ether gave 0.4 g (contained 15.1 % of the branch product). Fraction of 20% ether gave 2.2 g pure. IR(ν, cm-1): 1652 (w, C = C),1140 (m, C – O), 1120 (m, C – O), 1080 (m, C – O), 1035 (s, C – O), 966 (m, C = C). 1H NMR (CDCl3, δ ppm): 0,89 dt (dt, J = 2,8; 6,7 Hz, 3H, CH3); 1,2 – 2,0 (m, 16H, CH2); 1,57-1,89 (m, 6H, CH2-tetrahydropyran); 3,25 (t, J = 6,7 Hz, 2H, H-1); 4,0 (m, 2H, CH2Otetrahydropyran); 4,58 (t, J = 6,6 Hz, 1H, OCHO); 5,35 – 5,45 (m, 2H, -CH=). 13C NMR ((CDCl3, δ ppm): 13,97 (C14); 19,75 (C3’); 25,51 (C4’); 26,17 (C3); 28,62 (C11); 28,91 (C4, C5); 29,11 (C6); 29,58 (C2); 30,79 (C2’); 31,85 (C12); 33,58 (C7, C10); 62.39 (C5’); 67,42 (C1); 98,92 (C1’); 130,33 (C8, C9). Acknowledgments:This work was supported from Nation Program of Fundamental Research - Ministry of Science and Technolgy, Vietnam. REFERENCES 1. Corey, E.J; Boaz, N.W. 1985. The reaction of combined organocuprate– chlorotrimethylsilane reagents with conjugated carbonyl compounds. Tetrahedron Lett. 1985 : 6019 – 6022.

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2. Fouquet, G.; Schlosser, M. 1974. Improved carbon – carbon linking by controlled copper catalysis. Angew. Chem. Int. Ed. 13 : 82 –83. 3. Gries, G.; Gries, R.; Perez, A.L.; Oehlschalager, A.C.; Gonzalez, L.M.; Pierce, H.D.Jr., Zebeyrou, M.; Kouame, B. 1994. Aggregation pheromone of the African rhinoceros beetles , Oryctes monoceros (Olivier) (Coleoptera : Scarabaeidae). Entomol. Exp. and Appl. 18 : 135 –140. 4. Hallett, R.H.; Perez, A.L.; Gries, G.; Gries, R.; Pierce, H.D.Jr.; Yue, J.; Oehlschlager, A.C.; Gonzalez, L.M.; Borden, J.H. 1995. Aggregation pheromone of coconut rhinoceros beetles, Oryctes rhinoceros (L.) (Coleoptera:Scarabaeidae). J. Chem. Ecol. Vol. 21, No. 10, 1549 – 1570. 5. Konno, Y., Arai, K., Sekiguchi, K., and Matsumoto, Y. 1982. (E)-10Hexadecenal, a sex pheromone component of the yellow peach moth, Dichocrocis punctiferalis Guenée (Lepidoptera: Pyralidae). Appl. Entomol. Zool. 17:207-217. 6. Mori, K., Watanabe, H., Fujiwhara, M., Kuwahara, S. 1990. (E)- and (Z)Tetradecenyl formate, potent sex pheromone mimics against the yellow peach moth. Liebig's Ann. Chem. 12:1257-1259. 7. Morin, J.P.; Rochat, D.; Malosse, C.; Lettere, M.; Desmier de Chenon, R.; Wibwo, H.; Descoins, C. 1996. Ethyl 4-methyloctanoate, major component of Oryctes rhinoceros (L.) (Coleoptera : Dynastidae) male pheromone. C. R. Acad. Sci. Ser. III, 319(7), 595–602. 8. Nathan A. Ross, Richard A. Bartsch and Alan P. Marchand. 2003. Highintensity ultrasound-promoted Reformatsky reactions of 2,6 3,10 5,9 pentacyclo[5.4.0.0 .0 .0 ] undecane-8,11-dione. Issue in Honor of Prof. Henry J. Shine. ARKIVOC 2003 (xii) 27-30 9. Nguyen Cong Hao, Dang Chi Hien, Nguyen Cuu Thi Huong Giang. 2003. Synthesis of (S) ethyl 4-methyloctanoate, the aggregation pheromone of Rhinoceros beetles (Oryctes rhinoceros Linn.). Journal of Chemistry, Vol.41, No.2, 125-127. 10. Nguyen Cong Hao, Nguyen Cuu Thi Huong Giang, Dang Chi Hien. 1995. Synthesis sex pheromone of Prays citri Milliire. Proceedings, National of Science and Technology in Organic Chemistry Congress, November, 2005. 11. Smith, D.H. 1999. Grignard reactions in “wet” ether. J.Chem.Ed. 76(10) 1427 -1428. 12. Smith, D.H. 1999. The Grignard Reaction Synthesis of a Tertiary Alcohol. J. Chem. Ed, 76, 1427-8.

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SUITABILITY OF OIL PALM FIBER AND KERNEL AS MEDIA IN DETERMINING OF OXYGEN DEMAND IN SUB-SURFACE FLOW OF CONSTRUCTED WETLAND Ahmad Md. Noor(a), A.Y. Siew(a), H.L.H. Chong(a), H.P.S. Abdul Khalil(b), S. Suryani(c) (a)

School of Chemical Sciences, (b)School of Technology Indsutry, (c) School of Distance Education, Universiti Sains Malaysia, 11800 Penang, Malaysia. [email protected]

ABSTRACT This study is to investigate the suitability of oil palm waste, which is oil palm fiber and kernel as a media to determine the value of oxygen demand in the subsurfaceflow (SF) constructed wetland. A reactor which was operated using gravel was used as reference. The results show that the tap water used as influent gave values of BOD5 1.1 – 1.4 mg/L and COD 0 – 30 mg/L. The effluent from reactors with media of gravel, oil palm fiber and kernel were analyzed to gave value of BOD5 0 – 1.4 mg/L and COD 0 – 30 mg/L; BOD5 56 – 92 mg/L and COD 195 – 328 mg/L; BOD5 243 – 307 mg/L and COD 1120 – 1400 mg/L respectively. After adding 10 mg/L Cu (II) into tap water, BOD5 and COD of the effluent show a decrease in early stage, but after a while, it gradually increase and return to the same level as before adding Cu(II). Continuous washing on the oil palm fiber and kernel will reduce the percentage of COD effectively. In conclusion, oil palm fiber and kernel which used as media were found to contribute to a higher value of BOD5 and COD. Adding in Cu(II) into the water sample did not affect the BOD5 and COD significantly except in the early stage. Keywords: Constructed wetland; oil palm waste; BOD5; COD; Cu(II).

INTRODUCTON Constructed wetlands made of mainly support medium, microorganism and vegetation. These components play their own ways of treating the wastewater. Constructed wetlands are used extensively in treating wastewater such as for domestic (Kadlec and Knight, 1996; Srinivasan et al, 2000), industrial wastewater (Hammer, 1989; Cooper et al., 1996), and highway runoff (McNeill and Olley, 1998). Normal support medium usually consist of gravel, sand, stone and others. No studies were found to use agricultural waste as a media in constructed wetlands for wastewater treatment. Malaysia as one of the world producer of palm oil has generated from palm oil industries solid waste estimated to be more than 10 millions of tones per annum consist of among others are empty fruit bunch (EFB) and palm kernel shell (Abdul Khalil et al., 2001). This waste should be utilized into various values added products instead of using as fertilizer in oil palm plantation and as fuel to boilers.

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The aim of this study was to utilize this waste as a media for wetland system to treat especially domestic wastewater. This paper presents the results of BOD5 and CODS removal performance using mesocarp fiber, oil palm kernel and gravel as filtration media to treat water and water spiked by copper sulfate solution. EXPERIMENTAL Three lab scale units of subsurface-flow (SF) constructed wetlands (CW) with horizontal flow characteristics were built using polypropylene tanks with the dimension of 66 cm long, 44 cm wide and 34.5 cm height. The media was filled into each reactors unit at a height of 31 cm. The inlet perforated tube was placed at the depth of 15 cm in the media at one end, while effluent was collected from overflow tap situated on the opposite end of the CW unit. The media constitute of mesocarp fiber, oil palm kernel and gravel. Prior for applying media sample into the reactors, both oil palm waste in the form of fibrous and shell (shell size of 3-8 mm in diameter) respectively, were washed by immersing in tap water for overnight and washed thoroughly with tap water to remove oil and dirt. These processes were repeated and carried out for three weeks. Finally, the fiber and kernel were put under the sun to dry and will later to be used as media in the CW system. Composition and capacity of media in CW reactors, flow rate and hydraulic retention time (HRT) for testing water sample are given in the Table 1. Table 1. Characteristic of the constructed wetlands. CW reactor Types of media Capacity, kg Flow rate, mL/min Retention time, days

I Oil palm kernel 32.6 6.48 5.8

II Oil palm mesocarp 7.3 6.48 3.6

III Gravel 106.9 6.48 3.0

Tap water and tap water spiked with 10 mg/L copper sulfate solution were used as the feed to each of the three systems and the performance of media in removing BOD5 and COD in the CW system was determined. Collection of test sample at inlet and outlet points were carried out in the morning, every day for ten days and the analysis of BOD5 and COD were done immediately according to the Standard Methods for the Examination of Water and Wastewater (APHA, 1992). Prior to analysis, the liquid sample was filtered through No. 1 Whatman filter paper to remove any suspended solids, dirt and impurities.Mesocarp fiber and kernel were again washed every day for 12 days with tap water and copper sulfate solution respectively. The COD concentration and pH of the filtrate were determined for every washing. RESULTS AND DISCUSSION BOD Performance The influent and effluent characteristics ranges and mean values for BOD5 are shown in Table 1. Influent BOD5 concentrations into the various media were in the range of 1.263-1.389 mg/L and the mean value was 1.218 mg/L, while the effluent was observed to be in the range of 0.025-1.737 mg/L and the mean value was 1.031 mg/L 125

for pea gravel. The mesocarp fiber and oil palm kernel show very much higher in the range of 56.20-91.76 mg/L, and 243.0-306.9 mg/L, with mean value 71.55 mg/L and 271.3 mg/L respectively. The increase of BOD5 concentration was due to decay of lignocellulose materials, the process that generate microorganisms and other elements which of high demand oxygen in their survival. This is in agreement to Scholz and Xu (2002). The value of BOD5 along the period of observation was not stable (Figure 1). Table 1. BOD5 influent and effluent characteristics in various media of CW (n = 10). Media

Influent Range Mean

Effluent Range Mean

Tap water Pea gravel 0.025-1.737 1.263-1.389 1.218 Mesocarp fiber 56.20-91.76 Oil palm kernel 243.0-306.9 Tape water spiked with copper sulfate solution Pea gravel 0.899-1.231 1.019-1.364 1.158 Mesocarp fiber 46.96-68.73 Oil palm kernel 112.5-306.9

1.031 71.55 271.3 1.105 56.18 202.2

350 300 BOD5, 250 mg/L 200 150 100 50 0 1

2

3

4

5

6

7

8

9

Day Inlet

Gravel

Mesocarp

Kernel

Figure 1. BOD5 of influent and effluent of constructed wetland of various media. When the influent’s tap water was spiked with 10 mg/L copper sulfate solutions, the results show that there are no change of BOD5 values for the influent and effluent of gravel. The result for BOD5 is shown in Figure 2. For mesocarp fiber, BOD5 values slightly decreases to about 47 – 59.5 mg/L. However, there are significant decreases in BOD5 (175 – 113 mg/L) for kernal in early stage up to five days, but immediately increases to 306 mg/L at 10th day. This performance probably due to the rate of microorganism metabolism in the media especially for kernel was retarded due to the toxicity of the Cu(II) solution. After five days, the present of toxic metal did not affect

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10

the BOD5 and this is shown by an increase its values to original as before the addition of copper solution.

350 300 BOD5, 250 mg/L 200 150 100 50 0 1

2

3

4

5

6

7

8

9

10

Day Inlet

Gravel

Mesocarp

Kernel

Figure 2. BOD5 of influent and effluent of constructed wetland media after spiked with 10 mg/L Cu(II) COD Performance Figure 3 shows the COD value for a similar system of CW. The performance of all media is in a similar trend as to the BOD5 results, the difference only in their magnitude. The COD value for the influent in the range as similar to the effluent of gravel which is 0 – 30 mg/L, follows by mesocarp fiber in the range of 195 – 328 mg/L. The value for kernel still contributed to very high value in the range of 1120 – 1400 mg/L (Table 2). This indicates that mesocarp fiber and oil palm kernel generated very high COD concentration into the effluent with unstable values along period of study (Figure 3). This result indicated that as for BOD5 was due to the decay of the lignocelluloses materials or possible of incomplete washing the media. Table 2. COD influent and effluent characteristics in various media of CW (n = 10). Media

Influent Range Mean

Effluent Range Mean

Tap water Pea gravel 0-30 0-30 8.5 Mesocarp fiber 195-328 Oil palm kerner 1120-1400 Tap water spiked with copper sulfate solution Pea gravel 3.4-37.7 0-17.1 8.7 Mesocarp fiber 150-334 Oil palm kerner 1200-1474

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11.7 254 1236 16.4 238 1325

1600 1400 1200 COD, mg/L 1000 800 600 400 200 0 1

2

3

4

5

6

7

8

9

10

Day Inlet

Gravel

Mesocarp

Kernel

Figure 3. COD of influent and effluent of constructed wetland of various media

1400 1200

COD, mg/L

1000 800 600 400 200 0 1

2

3

4

5

6

7

8

9

10

Day Inlet

Gravel

Mesocarp

Kernel

Figure 4. COD of influent and effluent of constructed wetland media spiked with Cu(II) The effect of spiking the tap water with copper sulfate solution to COD values of influent and effluent are shown Figure 4. COD value for influent shows some decrease but no significant changes for effluent for all media. This is to indicate that the present of copper sulfate solution in the effluent did not affect their COD concentration. The reason for spiking copper sulfate solution into the tap water sample was to improve the media performance in removing BOD5 and COD. Unfortunately, from the result shown above indicated that there was no significant effect to the media except for gravel. Effect of washing mesocarp fiber and oil palm kernel Mesocarp fiber and oil palm kernel used as media in the CW gave very high value of BOD5 and COD, although the water sample used in this test was spiked with copper

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sulfate solution. This probably due to incomplete washing of the media, where some oil still remain in the fiber and kernel. To overcome to this possible problem, again the mesocarp fiber and oil palm kernel were washed repeatedly with distilled water and solution of copper sulfate for 12 times (every day for 12 days). The kernel used was reduced to smaller size to 3 – 5 mm from 3 – 8 mm. The results on the effect of washing was limited for observation to COD concentration and pH value of the effluent and are shown in Figures 5 and 6, while the average values are given in Table 3. Table 3. COD and pH of effluent after the media washed 12 times with water and copper sulfate solution. Media

Distilled water

COD Mesocarp fiber Oil palm kernel pH Mesocarp fiber Oil palm kernel

10 mg/L copper sulfate solution Range Mean

Range

Mean

12.0-231.4 0-81.0

45.1 15.9

6-246 0-64.3

41.5 15.1

5.15-6.53 4.13-6.12

5.84 5.24

3.18-5.91 2.55-5.86

4.75 4.57

300

250

200

COD, mg/L 150

100

50

0 1

2

3

4

5

6

7

8

No. of washing Distilled water

(a)

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Cu(II) sol.

9

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12

90 80 70 COD, 60 mg/L 50 40 30 20 10 0 1

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3

4

5

6

7

8

9

10

11

12

No. of washing Distilled water

Cu(II) sol.

(b)

Figure 5. Effect of washing media (a) mesocarp fiber (b) oil palm kernel on thE COD value of effluent Figure 5 and Table 3 show a tremendous drop of COD concentration after the media was repeatedly washed with distilled water and copper sulfate solution. However, washing media with copper sulfate solution did not significantly affect the COD value. When the size of kernel was reduced to smaller size, it helps greatly to lower the COD concentration. Six to eight times washing of the media reduced the COD to about 20 mg/L for mesocarp fiber while for kernel to be about less than 5 mg/L.

7

6

pH 5

4

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0 1

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No. of washing Distilled water

(a)

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Cu(II) sol.

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4 3 2 1 0 1

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7

8

9

10

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No. of washing Distilled water

Cu(II) sol.

(b)

Figure 6. Effect of washing media: (a) mesocarp fiber (b) oil palm kernel on the effluent pH value. Figure 6 shows that the number of washing after 8 times will make the effluent from both media to be more acidic with the pH were less than 5. Washing with copper sulfate solution will make effluent more acidic compared to distilled water. The lowest COD value for effluent from both media is observed at pH 5 – 6 at the number of washing at 6 – 8 times. CONCLUSION The concentrations of BOD5 and COD of the effluent that passed through mesocarp fiber and oil palm kernel as constructed wetlands media were found to be higher than the values of influent. The tap water as influent was spiked with copper sulfate solution did not help to reduce BOD5 and COD values. However, when the media again been washed many times with distilled water and copper sulfate solution and the size of the kernel was reduced to smaller range of 3 – 5 mm there shows tremendous drop on the COD value to about 20 mg/L for mesocarp fiber while for kernel to be about less than 5 mg/L, which is lower than the value for tap water as influent with range 0 – 30 mg/L. The optimum performance of media was at the pH of the effluent to be at pH 5 – 6. Acknowledgement This study is supported by IRPA grant 305/PKIMIA/610810, Kementrian Sains, Teknologi dan Alam Sekitar Malaysia and the Universiti Sains Malaysia. References Abdul Khalil, H.P.S. Ismail, H. Ahmad, M.N., Ariffin, A. and Hassan, K. (2001). The effect of various anhydride modification on mechanical and water absorption properties of oil palm empty fruit bunches reinforced polyester. Polymer International. 50, 1-8.

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