本文旨在探討桃園地區硫沈降之時空分布特性，以了解桃園地區污染源所排放之SO2對桃園地區之酸雨的貢獻。吾人修改ISC (Industrial Source Complex)模式，並以1997年為基準年，模擬桃園地區固定污染源SO2之排放、擴散、傳送與沈降。 清除係數(λ)為影響溼沈降量的重要參數，估算一個適合桃園地區的清除係數，將有助於模式對溼沈降模擬的準確性。以降雨期間，空氣中污染物濃度隨時間變化來求得清除係數λ，並由迴歸分析獲得λ與降雨強度P的關係式λ=7×10-5 P0.58，將此關係式應用於ISC模式中，以供模式對溼沈降更準確的模擬。 桃園SO2排放源資料尚不完整，吾人利用統計方法(統計分析、迴歸分析、相關性分析及聚類分析)推估模式所需的排放參數，以完成本文所模擬的1138筆SO2排放資料。SO2濃度模擬與監測結果比較發現，模式可模擬出SO2濃度逐月變化的趨勢，並對於出現濃度高值與低值的月份幾乎都可掌握到，但在定量上有低估的現象。 吾人將SO2固定排放源分為A(林口發電廠)、B(中油煉油廠)、C(其他中小型排放源，分成10個行業別)三組。模擬結果顯示：大型排放源如A、B兩組所能擴散的範圍較廣，所以地面濃度被稀釋，而小型排放源C組雖然擴散範圍較小，但能形成局部高濃度，對於酸沈降的貢獻，不容忽視。固定污染源對桃園地區硫溼沈降貢獻量方面， A、B、C三組間的比值約為5：3：12。硫溼沈降量模擬值與觀測值比較發現，模式可模擬出觀測的極值，但在定量上有明顯低估的現象。 The purpose of this study is to investigate the sulfur deposition distribution, and contribution SO2 point sources in Taoyuan County. In the study, ISC (Industrial Source Complex) Model was modified to simulate SO2 emission, dispersion, transport and deposition in Taoyuan country, based on 1997 emission inventories. Scavenging coefficient λ is an important parameter of determining wet deposition. It is in the form of , where C is the SO2 concentration in air. Our data showed that λ and precipitation intensity P have a relationship of λ=7×10-5P0.58. Because the SO2 source data was not completed for model inputs, Statistical methods were applied to evaluate the missing parameters. As a result 1138 point source data were used for modeling. Comparing with the measurements, modeled SO2 concentrations are qualitatively in a good agreement, but underestimate. These 1138 point sources are divided into 3 categories, A (Lin-kou Power Plant), B (China Petroleum Refinery), and C (Other stacks). Large sources such as A and B can contribute widely the SO2 dispersion but make the lower surface concentration. Category C makes an opposite situation, and its influnce can’t be neglect. The ratio of these three categories to wet deposition was about 5:3:12. The model can simulation deposition pattern, but underestimate the values.
