大氣的懸浮微粒(Particulate Matter；PM)不僅影響全球空氣品質及氣候變遷，且日益嚴重， PM的監測因此成為國際上重要的議題。目前對於PM的觀測，仍以地面測站為主，由於PM時空分布的特性非常明顯且地面測站的分佈不均，限制其在完整空間分佈資訊之提供；而衛星資料雖能提供大範圍的相關觀測，但在缺乏氣膠垂直分佈資訊的情況下，無法推估近地表PM濃度之訊息。因此本研究藉由地面觀測資料考慮相關影響因子(垂直分布、種類及水氣影響)，分析氣膠光學厚度(Aerosol Optical Depth；AOD)與PM濃度之關係，期能應用於衛星遙測資料，以獲得大範圍PM濃度分佈之資訊。 一般而言，懸浮微粒垂直分布之獲取不易，由於PM的變化量主要集中於近地表區域，本研究藉由衛星觀測之氣膠光學厚度(AOD)的變化量主要為進地表PM變化所致之假設，嘗試克服垂直分布獲取之限制。除垂直分佈外，氣膠種類及水氣是影響AOD與PM關係的主要因素，藉由氣膠種類(沙塵粒子、人為污染物及生質燃燒)辨識後，再納入相對濕度修正後，分別建立AOD與PM變化量之關係，研究結果顯示，沙塵粒子、人為污染及生質燃燒的相關係數分別為0.71、0.73及0.81。將所建立之轉換模式應用於台灣地區MODIS AOD產品進行測試，其相關係數可高達0.92、方均跟差為7.60 ，說明了本研究方法之可行性，對於後續衛星觀測在大範圍下PM濃度之效益非淺。 ;Since the impact on global air quality and climate change are obvious and serious gradually, the observation of Particulate Matter (PM) has become essential issue all over the word. Due to the location of ground station and the large variance, the complete PM observation in spatiotemporal distribution has its limitation. Although satellite can provide widely observation, the short of information of aerosol vertical distribution is not satisfied to provide the surface PM concentration. Therefore, this study aims at the investigation of the relationship between aerosol optical depth (AOD) and PM from ground measurement with considering the key factors (vertical distribution, type and humility). Eventually, the results can be expected to benefit to a regional monitoring of PM concentration by means of satellite observation. To overcome the difficult of vertical distribution, this study assumes that the variation of total column AOD observed by satellite sensor is principally caused from the variation of PM near surface level. Then factors of aerosol type and water vapor effect are taken into account for the relationship between AOD and PM. Aerosol types of dust, anthropogenic pollutants and biomass burning are the main species of PM in this study. After the correction of water vapor effect, the correlation coefficients between △AOD and △PM based on the ground-based measurements are 0.71, 0.73 and 0.81 for dust, anthropogenic pollutants and biomass burning respectively. The results are further applied to MODIS AOD products in Taiwan. The root mean square error (RMSE) is 7.60 after compared with ground measurements, indicating highly feasibility of proposed approach for PM concentration monitor from satellite remote sensing.