量化環境及生態因子對多氯聯苯在熱帶河口魚體體內分佈影響之研究

• Main Authors: 傅崇德, Fu, Chung-Te
• Other Authors: 吳先琪, 臺灣大學：環境工程學研究所
• Format: Thesis
• Language: English
• Published: 2006
• Subjects: 多氯聯苯; 二仁溪河口; 生物累積:魚; 量化; PCBs; Er-Jen estuary; bioaccumulation; fish; quantification; Arctic
• Online Access: http://ntur.lib.ntu.edu.tw/handle/246246/62600; http://ntur.lib.ntu.edu.tw/bitstream/246246/62600/1/ntu-95-D90541001-1.pdf

持久性有機污染物由於在環境中具有持久性、毒性、累積性及長程輸送等特性，造成其在全球不同生態系統的生物體內之累積現象及危害，因此引起國際社會之重視並謀求解決之道。國外針對此一生物累積現象已有許多相關之研究，但是這些研究多半著重於水質相對穩定之內海或湖泊等生態區域內，和本地已知之污染區域多數位於水質變動之河口區域有所不同；且國外所研究之區域多數是屬於溫帶至寒帶區域，其生態系統和台灣本地處於熱帶或亞熱帶氣候區域之生態勢必有所差異。在考量不同氣候環境及生態系統之差異下，本研究之主要目的在探討環境及生態因子對持久性有機污染物在亞熱帶河口地區之生態系統內分布情形之影響，並特別著重暴露於底泥的水棲生物之累積特性及累積程度之探討。在本研究中，選定台南二仁溪流域作為研究區域，並以多氯聯苯為研究標的物。考量之影響因子則包括豐枯水所造成之季節性變異、生物棲地之差異、物種及營養階層間之差異以及持久性污染物之物理化學特性等。藉由在二仁溪流域及鄰近區域內所採取之底泥及魚類樣品之濃度及指紋圖譜，建立底泥和底棲攝食性魚類中多氯聯苯來源之相關性；同時透過營養階層和攝食習性之差異，建立魚體體內多氯聯苯暴露量之模式。 本研究分析2002至2004年雨季前後在二仁溪流域中所採取之底泥及大鱗鮻(Liza macrolepis)之多氯聯苯的含量及同源物分佈，發現與降雨後河口區域之底泥中多氯聯苯含量及低氯數同源物種之比例有同時增加之現象，顯示雨季後所造成底泥中多氯聯苯型態之改變，反映至以底泥為主要食物來源之魚體體內，亦表示底泥是居住在此受污染河口之水棲生物的主要多氯聯苯暴露來源。為更進一步證實此論點，分別採取河口區域附近之養殖池及安平港航道內之大鱗鮻魚體樣本，發現二仁溪河口之魚體樣本會因為棲息於受污染嚴重之生態系統而有顯著較高之體內含量，而養殖池之樣本體內具有最低之污染物負荷及較高之低氯數物種，表示其未與受污染之底泥直接接觸，所以主要之暴露途徑為經由大氣輸送。安平港航道內之樣本則因為其污染年代較久而具有最高之高氯數物種比例。經由不同棲地之特性所觀察到之魚體體內濃度及型態，可以推論出大鱗鮻體內之暴露途徑受棲地之影響，同時佐證河口滯留型魚體之暴露途徑主要來自於受污染之底泥。 本研究同時以光纖作為介質以量測污染物之活性及傳輸方向，結果顯示污染物之傳輸方向為由底層底泥向表層底泥，然後擴及水體及水棲生物體內。此再次驗證前述污染物之累積途徑及累積程度之差異。 兩大類十種不同營養階層的魚種，包括虱目魚(C. chanos)、鯔魚(M. cephalus)、環球海鰶(N. come)、大鱗鮻(L. macrolepis)、班海鯰(A. maculates)等底棲生活性魚種，以及布氏金梭魚(S. putnamiae)、白帶魚(T. lepturus)、海鰱(E. machnata)、大甲鰺(M. cordyla)及大眼海鰱(M. cyprinoides)等上層迴游性魚種之分析結果顯示，底棲攝食性魚種之體內多氯聯苯累積量隨其營養階層增加而增加。多氯聯苯同源物在魚體體內和底泥內之比值(BSAF) 隨KOW值增加而增加，其中並以logKOW值在6.5至7.0之間的同源物種累積量最高，表示物質之疏水性是影響其累積程度之重要因子。但是logKOW值大於7.0之同源物種的累積量會逐步下降，其累積量下降之原因可能是因為這些物質受到結構阻力，而造成其在動力上較不易進入生物體內，同時因為代謝較慢而未及進入體內便被排泄掉而減低其累積量。 依據前述研究所得污染物之傳輸方向，本研究利用生物消化腔放大倍率半經驗式及簡化之逸壓平衡模式來推估由底泥暴露至魚體內多氯聯苯之累積量。本研究生物消化腔放大倍率半經驗式所求得之結果為 (r2 = 0.90)。所求得不同同源物之放大倍率在log KOW小於7時和Gobas等人(1993)之結果相近，約在1.4至3.8倍之間。但是在log KOW大於7時則較低，其原因則可能是因為這些高KOW物質具有較低之吸收速率或較高之進入細胞的結構阻力而使體內之逸壓小於排泄物之逸壓，同時造成本研究所得之放大倍率較Gobas等人以排泄物中含量代表體內含量之觀測值為低。逸壓平衡模式由於最具有理論基礎，所以應用性也最高，但必須輸入大量之模式參數。由預測值和觀測值之間的回歸直線斜率接近1(1.33)，顯示其預測結果有相當之參考性。 本研究所得之結果，不論是在建立魚体和底泥之間之暴露途徑、食物鏈之累積特性或是預測模式之發展，對於未來在預測污染物之傳輸、評估消費者之風險及訂定底泥整治基準上，均提供了相當重要之貢獻。 Polychlorinated biphenyls (PCBs), a group of persistent organic pollutants (POPs), with high bioaccumulation potential and hazard to biota become a world-wide concern. Most previous studies were conducted in the regions where hydrological conditions and water qualities vary slightly compared to in the local estuaries in Taiwan, where water conditions fluctuate significantly. Also the climate in Taiwan is different from those in the temperate and sub-polar regions, which might lead to distinguishable distribution patterns of POPs in ecosystem. The severe contamination of PCBs in Er-Jen River in southwestern Taiwan in early 1990s has raised the concern of how and to what extent the PCBs has affected the ecological system in the estuary. To clarify the phenomenon of bioaccumulation in these biota and for further prediction of their PCBs body burden by quantification models, the purposes of this study are to unveil the origins of the PCBs and to distinguish the characteristics of food web biomagnification within the biota in the estuarine region. Furthermore, this study has also tried to develop a gastrointestinal tract magnifying model and a fugacity model to predict the body burden in biota. Additionally, a modified SPME technique has been applied to measure the activity of chemicals. To identify the origins of PCBs in the fishes residing in the estuary, this study has investigated some physicochemical parameters of the river system and PCB concentration of the river surface sediment and L. macrolepis before and after wet seasons in year 2002 to 2004. Obvious increment of PCB content and significantly elevated fraction (p < 0.005) of light PCBs of the river mouth’s sediments after each wet season indicates that the invading particles were rich in unweathered PCBs. PCBs previously buried in the soil of heavily contaminated sites were flushed into this estuary through surface runoff. Precipitation led to certain PCB patterns, significantly greater fraction of light PCBS in sediment organic matter, the dietary source of mullet, and consequently the same in mullets. The seasonal variation of the distribution of PCBs on surface sediments help us to establish the link between surface sediment and bottom dwellers. In addition to the hydrological variation, variation of PCB concentration among habitats has confirmed that the source of PCBs in biota was originally from the sediment. The PCB body burden of collected fish samples was proportional to the contamination level of their locations. Using the less chlorinated PCB fraction (triCB + tetraCB) / total PCBs as the indicator of the origins of PCBs, fish near former contaminated areas had greater body burdens of the more chlorinated PCB congeners, while the farmed fish exhibited a PCB pattern more like that known to originate from air-water exchange with less chlorinated PCBs predominating. The deviation of concentration and congener profile in the three habitats indicate that these variations are attributed to their habitats, and sediment was the most possible source of PCBs to fish. A modified SPME technique was applied to detect the aqueous equivalent content (AEC) of polychlorinated biphenyls in field samples. Indicated by the gradients of activities of concerned compartments, the bottom sediment was the source of contaminant in this estuary, and PCBs moved from buried sediment to surface sediment, to water column and finally to the biota. The fishes in this estuary included bottom dwellers such as C. chanos, M cephalus, L. macrolepis, N. come and A. maculates, and some pelagic dwellers such as M. cyprinoides, E. machnata, T. lepturus, S. putnamiae and M. cordyla.M. The bioaccumulation through food web in the bottom dwellers increased with their trophic levels, while for the pelagic dwellers the phenomenon was unseen. The biomagnification found only in these sediment-linked fishes suggests that the surface sediments are the main source of PCBs in the estuary. The biota to sediment accumulation factor (BSAF) of individual PCB congener was directly in proportional to their chlorination degree and increased with elevated trophic level, which indicates that the more hydrophobicity of the chemicals, the higher accumulation potential they will possess. The chemical with the highest accumulation potential was those with log KOW in the range 6.5 to 7.0. The trend decreases when log KOW exceeds 7. Biomagnification of the highly hydrophobic congeners are not increasing with their KOW. Structural hindrance and other unidentified factors may retard the partition of chemicals into the cells of biota. Predictions of the PCB concentration of total body burden and individual congeners were performed by the GIT biomagnification model and the simplified fugacity model. The possible slope of the predicting formula based on the GIT model, (r2 = 0.90), reveals the tendency of bioaccumulation of PCBs through trophic levels. The magnifying ratios of PCB congeners with log KOW range from 5.5 to 7.0 are around 1.4 to 3.8, similar to the findings in Gobas et al. (1993), but smaller than Gobas’s observation for the congeners whose log Kow are larger than 7.0. This was attributed to that the higher fugacities measured by Gobas were from the feces rather than the tissue, which led to an overestimation of magnifying ratio. The ratio between observed values and predicted values data from the simplified fugacity model, though in which numerous parameters are necessary, is close to 1.0 (1.33), which reveals the accuracy of the model. This study has not only established the exposure route of PCBs to fishes in a local estuary case, but also provided predicting models for the body burden of PCBs in fishes. These research results will considerably help on the risk management of POPs in local and other cases, setting criteria of sediment qualities and choosing sediment remediation approaches 1. Introduction 1 2. Background and theories 3 2.1. General introduction of polychlorinated biphenyls (PCBs) 3 2.1.1. Physical and chemical properties of PCBs 3 2.1.2. Toxicity of PCBs toward Human. 4 2.1.3. Distribution of PCBs in environment 8 2.1.4. Factors controlling the fate of PCBs in environment. 10 2.3. Habitat variation on the PCB body burden of fish 18 2.4.1. Determination of trophic level 21 2.4.2. Bioaccumulation and trophic level transfer 25 2.5. SPME-detected chemical activity and their applications in estimating the distribution of POPs in an ecosystem 27 2.6. Bioaccumulation models for POPs in fish 33 3. Method and Material 43 3.1. Samples collection 44 3.1.1. Sediment samples 44 3.1.2. Biota samples 45 3.3. Preparations and sampling with SPME 51 3.3.1. Preparation of extracting fibers 51 3.3.2. Sampling conditions. 52 3.3.3. Analyses of PCBs sorbed in fiber. 53 3.4. Development of gastrointestinal tract magnifying model 53 3.5. Development of the simplified model for predicting PCB level of sediment dweller in estuary 55 4. Results and Discussions 63 4.1. Verification of exposure route between sediments and fish through the seasonal variation of PCBs 63 4.1.1. Seasonal change of the water quality in Er-Jen estuary 63 4.1.3. PCB concentrations of sediments 67 4.1.4. PCB pattern deviation in sediment 69 4.2.1. General information of fish samples 79 4.2.2. PCB concentration 79 4.2.3. Congener profile 84 4.3.2. The relationship of PCB concentration in fishes to their trophic level 94 4.3.3. Congener profiles within fishes 103 4.3.4. Biota to sediment accumulation factor 109 4.4.1. Exposure kinetics. 114 4.4.2. Available equivalent concentration of water, sediment and fishes 119 4.4.3. Equilibration evaluation of water, sediment and fish by their AEC ratio. 125 4.5.1. Prediction of total PCB body burden of fishes 127 4.5.2. Prediction of concentrations of PCB congeners in fishes by magnifying ratio 128 5. Summary 141 5.1. Summary of results and finding 141 5.2. Future prospect 144 Reference 147 Appendix A