氣膠不僅會影響全球氣候變遷，其對於人類身體健康亦會造成相當的危害，因此近年來空氣品質的監測已成為人們所關注的重要議題。其中與人類生活息息相關的近地表氣膠資訊雖然能夠透過地面測站之觀測獲得，然而其資訊卻受到地面測站的位置所限制，相反地，衛星雖然能夠進行大範圍的觀測，並且可以提供整層大氣總和的氣膠分布資訊，卻無法掌握漂浮於近地表的懸浮微粒(PM)，其中最為關鍵的原因便在於氣膠垂直分布訊息之缺乏，本研究延續李等人(李，2016)之研究，改善其對於氣膠單峰消光廓線之擬合與近地表氣膠資訊之反演結果，並分析本研究方法之可行性。 對數常態分布擁有與單峰型態的氣膠消光廓線相似的特性，本研究根據十年的MPLNET觀測資料，藉由程式擬合與迴歸分析所建立之氣象參數(氣膠光學厚度AOD、行星邊界層高度PBLH)與對數常態分布參數(對數平均數μ、對數標準差σ)之間的轉換關係式，同時為了更準確掌握近地表之氣膠資訊，根據近地表消光係數之比較結果設定地表層高度(Surface Layer Height)，成功建構出完整的氣膠單峰消光廓線之繪製方法。結果分析部分，在一整天皆為單峰的情況下，本研究方法繪製之廓線結果與實際觀測資料的比較結果大致皆可以達到0.9以上的相關係數，同時在近地表消光係數之反演方面，本研究反演結果與實際資料亦達到0.8973的相關係數，驗證了本研究方法之可行性。最後本研究透過結合衛星觀測及氣象模式資料，成功將台灣地區二維平面的氣膠資訊進一步以三維空間的分布呈現，並且在與懸浮微粒濃度之相關性分析結果中，驗證了透過本研究方法取得之氣膠垂直分布資訊，確實能夠改善衛星在近地表氣膠資訊之反演結果，同時也對於台灣地區空氣品質之監測有所助益。 ;Aerosols can not only affect climate change but also human health seriously. Therefore, the monitor of air quality has become an important issue in recent years. Although we can obtain the information of aerosols near surface from ground observations, which related to public health, it is still limited by the sites of stations. Satellite remote sensing can provide the total column aerosol information over a wider spatial range than ground-based point measurements, but the information near surface is still restrictive by the vertical distribution of aerosols. Therefore, this study continued the study of Lee, 2016, aimed at improving the mapping of aerosol extinction profile for the information of aerosols near surface. Because of the similar pattern between log-normal distribution and aerosol vertical distribution with single-peak conditions, regression analysis has been used to construct the relationship between meteorological data (Aerosol Optical Depth, AOD and Planetary Boundary Layer Height, PBLH) and log-normal variables (μ and σ) based on ten-years dataset from MPLNET (Micropulse Lidar Network). Besides, we determined the Surface Layer Height according to comparison result of near surface aerosol extinction in order to improve the accuracy of aerosols near surface layer. The correlation coefficients between mapping results after improvements and observation data are almost up to 0.9 under single-peak conditions. The correlation coefficient of surface layer extinction also reaches up to 0.8973. Then the proposed method was further applied to satellite observation and model simulation data in mapping extinction profile around Taiwan for the 3D spatial distribution of particulate matters (PM) concentration. The correlation results between surface extinction and PM concentration indicated high feasibility of proposed method in mapping the vertical distribution of aerosols surface PM retrievals by means of satellite remote sensing, as well as facilitated to the monitor of air quality.
