本研究目的主要以預測接著劑使用於複層建材之逸散特性及推估係數。樣本使用非綠建材之乾式建材(底材)加接著劑(基材)搭配乾式建材(面材)之複層建材組構型式,透過小尺寸直讀量測系統於標準狀態下且測試不同溫度條件(25℃、35℃),進行甲醛(HCHO)及總揮發性有機化合物(TVOC)定量分析。 結果顯示,複層建材之甲醛及TVOC有三階段逸散特性,且溫度越高逸散速率越高,35℃甲醛逸散速率約為25℃之1.97倍,35℃TVOC逸散速率約為25℃之1.34倍,影響複層建材之甲醛逸散速率多來自於表面材(木皮板);而TVOC則多來自於基材(強力膠)。本研究建立由單一建材推估複層建材中底、基、面材之單一建材逸散速率推估係數,及建立不同溫度下甲醛及TVOC高濃度與低濃度逸散衰減推估公式,可由25℃之單一建材推估25℃及35℃之複層建材逸散速率。基材由25℃升高至35℃,甲醛逸散係數約上升6%,而底材之逸散係數下降約1%,面材之逸散係數則約下降3%;而TVOC部分,基材由25℃升高至35℃,逸散係數約上升1%,而底材及面材逸散係數平均約下降1%。透過逸散衰減推估公式與實際量測之複層建材數據比對分析,大多於平均百分誤差之「預測準度優良」之範圍內,具有良好之推估敘述能力。
The objective of this study was used emission from multi-layered building materials(multi-layered BMs) to predict adhesive emission coefficients. We used the Multi-Layered of adhesive(Sandwich Materials) between the dry building material(Substrate Materials) and dry building material(Surface Materials).The Small Scale Chamber System was ventilated with conditioned air, temperature :25℃、35℃ and humidity 50%, air change rate 0.5 h-1.To assay to formaldehyde(HCHO) and Total Volatile Organic Compounds (TVOC). The result showed that had three Characteristics of TVOC and HCHO .The high temperature had stronger effect for chemical emission. The formaldehyde emission on 35℃ is higher than 25℃(1.97 folds), TVOC emission on 35℃ is higher than 25℃(1.34 folds). There had similar concentration with Multi-Layered BMs and surface material (1.2 folds), HCHO emission in Multi-Layered was major from Surface material (Engineered Wood), and TVOC are Sandwich Material(superglue). The study establish Predicted Coefficients for Multi-Layered BMs of Substrate, Sandwich, Surface materials, and understand Predicted Coefficients for Multi-Layered BMs on 25℃ and 35℃. The temperature from 25℃ rise to 35℃,the Sandwich material of formaldehyde emission increased 6%, the Substrate material decreased 1%, the surface material decreased 3%, the temperature in 25℃ to 35℃,the Substrate material of TVOC emission increased 1%, the Substrate material and surface material decreased 1%. This study through compare the emitted predicted value with experimental data, most of the values are 「Excellent Predictive Accuracy」in MAPE.