目標：煙道粒狀物濃度量測的準確性受到許多因素的影響，這些因素包括排氣速度、溫度、含水量、粒狀物濃度、採樣儀器的種類、甚至採樣人員的訓練與經歷等。而本研究的目的即是在於釐清可能的因子對於量測變異的貢獻程度，冀能針對主要的影響因子探討可能的誤差來源並加以改善。其次藉著因子分析的結果建立煙道粒狀物濃度之統計模型。方法：建置一套模擬煙道，主要由一內徑60 cm、高13.4 m之不?袗?管、一具15匹馬力的風車，以及前後進氣與出氣口之過濾設備所組成。此風扇最高可造成每秒15米的風速。粉塵的產生主要將利用一粉塵飼餵器(Palas powder disp erser)進行，此儀器可藉由輸送帶速度的調整來控制粉塵的濃度。一具750 kW的熱風發生器可將排氣溫度揚升至150oC，此外，煙道內的排氣濕度藉由一具120 kW的蒸汽產生器來調整，含水量可控制在2至10%的範圍。在研究中主要的操作變項有：粉塵濃度、溫度、濕度、風扇轉速(風速)等。研究中首先邀請八家環檢所檢定合格之代檢業參與資料庫的建立以初步界定各因子之影響程度。結果：從變異數分析的結果得知，排氣速度是影響煙道內粒狀物平均濃度量測的主要因子，其次分別為粉塵供應率、以及風扇轉速和含水量的交互作用，至於排氣溫度與排氣濕度的影響並未達統計 上顯著的水準。結論：本研究中建立了影響煙道內粒狀物濃度量測結果的初步模型，未來需進一步收集數據以檢驗該模型的適用範圍以及提升該統計模型的精準確度。

　　　　　Objectives: It is speculated that the dust concentration measurement is influenced by the interactions among exhaust velocity, temperature, humidity, dust concentration level, type of sampling equipment and trained and experienced members of sampling team. The results of this work can be used in the identification of the factor(s), which contribute to the variability of measurement results from ducts and stacks. Another objective of this study is to establish a statistical model to predict the mass concent ration of particulate matter in the stack. Methods: This testing system simulating a stack is composed of an inlet filtration unit, a 15-Hp blower, a 13.4-m height, a 60-cm diameter stainless steel duct, and an outlet filtration unit. The blower is capable of propelling the gas to reach the face velocity of 15 m/sec. A dust feeder, the Palas Powder Disperser, is used to generate aerosol particles. A heater of 750 kW with a feedback system is used to control the temperature of the exhaust gas. A 120 kW stea m generator is used to change the humidity of the exhaust gas, i.e., water content ranging from 2% to 10%. The major operation parameters include dust concentration, temperature, relative humidity, and fan rotation speed. Results: According to the analysis of variance, the duct velocity is the most influential operation factor, followed by dust feed rate, and the interaction of duct velocity and water content in determining the aerosol concentration in the stack. However, neither temperature nor water cont ent of the exhaust gas showed any significant effect. Conclusions: A statistical model for predicting mass concentration of particles in the stack was established. However, it needs further study before application. (Chin J Public Health.