河川流域重金屬與有機特徵物質污染源鑑識研究-以宜蘭新城溪為例
| 中文摘要 | 為瞭解水污染源對於河川水體與底泥品質之影響，本計畫於宜蘭新城溪進行具時空分布性之水體與底泥採樣工作，並搭配事業廢水採樣以獲得具事業代表性之污染源指紋圖譜(profile)，透過模式統計分析方法以評估水污染源對於河川水體與底泥污染物濃度特性之影響。計畫工作內容已完成：(1)國內外相關文獻整理: 包含國內外其他河川水體與底泥污染物檢測濃度、水污染源指紋圖譜資料，以及污染源鑑識模式之應用; (2)事業廢水採樣和檢測分析: 包含7種行業別和2間污水處理廠之廢水特性調查、事業廢水採樣工作與檢測分析，總計30點次; (3)事業廢水區判分析: 建立事業廢水之特徵物質; (4)河川水體與底泥採樣和檢測分析: 在不同季節於潛在污染來源之上下游進行河川水體與底泥採樣並檢測重金屬與有機物質等污染物，分別總計60和30點次。河川水體第一次和第二次採樣之重金屬相關污染物最大平均濃度為硫酸根 (993.47 mg/L和1342.11 mg/L)，第一次和第二次戴奧辛類多氯聯苯最大平均濃度為2.68 pg/L和6.77 pg/L。底泥第一次和第二次採樣之重金屬相關污染物最大平均濃度為鉛元素(9205 mg/kg 和7680 mg/kg)，第一次和第二次戴奧辛類多氯聯苯最大平均濃度為153.06 pg/kg和224.5 pg/kg; (5) 評估河川水體與底泥污染物之時間和空間分佈特性: 結果顯示河川水體與底泥之污染物熱區大部分於龍德大排，少部分於龍德與豐祥大排交匯處及三大排匯流處，部分採樣點之污染物濃度超過法規底泥標準之上限值，污染熱區的河川水體與底泥污染物濃度具有時間變異性; (6)河川水體污染物來源解析: 對於河川水體重金屬相關污染物和戴奧辛多氯聯苯，第一次採樣和第二次採樣之模式解釋百分比分別介於31.4%到105.7%，發現部分行業別製程廢水和未知污染源對河川水體有所影響，同時推估疑似污染源之可能位置，以提供後續工作進行調查與追蹤 ; (7) 河川底泥污染物來源解析: 底泥重金屬污染源解析結果不佳，有待進一步採樣檢測以提升污染源鑑識能力; (8)提出一污染源鑑識方法草案，以提供後續污染源鑑識計畫之應用。 | ||
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| 中文關鍵字 | 事業廢水檢測、河川水體污染、底泥污染、污染熱區評估、污染源鑑識模式 | ||
基本資訊
| 專案計畫編號 | EPA-106-S3E4-02-05 | 經費年度 | 106 | 計畫經費 | 2660 千元 |
|---|---|---|---|---|---|
| 專案開始日期 | 2017/04/07 | 專案結束日期 | 2017/12/31 | 專案主持人 | 王根樹教授 |
| 主辦單位 | 環檢所 | 承辦人 | 許元正科長 | 執行單位 | 國立臺灣大學環境衛生研究所 |
成果下載
| 類型 | 檔名 | 檔案大小 | 說明 |
|---|---|---|---|
| 期末報告 | 期末報告_Ho09.pdf | 10MB |
Source apportionment of metal elements and organic compounds in a river: a example at Sincheng River in Yilan, Taiwan
| 英文摘要 | This project attempted to investigate spatial and temporal distributions of water pollution sources and their impacts on the quality of river water and sediment. Seasonal stratified water and sediment samples were collected from multiple sites at the Sincheng River in Yilan County. Source profiles were obtained from sampling and analysis of industrial waste water. Source contributions to river water and sediment were estimated by statistical and modeling analysis. The works of this project were summarized as follows: (1) Literature review: analytical results of pollutants in river water and sediment, water pollution source profile, and application of source apportionment models were reviewed and summarized; (2) Sampling and analysis of industrial waste water: a total of 30 samples from 7 industries and 2 sewage treatment plants were sampled and analyzed; (3) Characterization of industrial waste water: specific markers of industrial waste water were identified; (4) Sampling and analysis of river water and sediment: a total of 60 water samples and 30 sediment samples were collected from the upstream and downstream areas of the potential pollution sources in different seasons, followed by analyses of heavy metals and organic compounds, including dioxins and polychlorinated biphenyls (PCBs). The maximam average concentrations of metal-related pollutants in the surface water were 993.47 mg/Land 1342.11 mg/L for sulfate during the first and second sampling periods, respectively. They were 2.68 pg/L and 6.77 pg/L for Dioxin-like PCBs. The largest average concentrations of metal-related pollutants were 9205 mg/kg and 7680 mg/kg for lead in the sediments and were 153.06 pg/kg and 224.5 pg/kg for Dioxin-like PCBs at the first and second sampling periods, respectively.; (5) Spatial and temporal distributions of pollutants in river water and sediment: temporal variations of pollutants were observed at several hotspots, especially the Loung Te main ditch which was identified as the most polluted hotspot; (6) Source apportionment of river water pollutants: the percent mass accounted for measured mass (%MASS) of modeling results ranged from 31.4% to 105.7% during the two monitoring periods. Potential sources of pollutants, including heavy metals, dioxins, and PCBs, and their possible locations were estimated for follow-up investigation; (7) Source apportionment of river sediment pollutants: potential sources of heavy metals were not well identified, indicating the need of improvement of source apportionment techniques; (8) Drafting a guideline for source apportionment of water pollution for future application. | ||
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| 英文關鍵字 | Industrial waste water, River water pollution, Sediment pollution, Pollution hotspot, Source apportionment | ||