| 摘要: | 暴露是指人與污染物質存在同一位置且與污染物質接觸的瞬間，主要由人與污染物兩因素之交互或共同形成，而暴露評估是一項必須完整記錄暴露過程以協助追蹤暴露來源的研究。任務本位暴露評估模式(Task-Based Exposure Assessment Model, T-BEAM)是一種著重於勞工特定工作任務與危害間關係的確認，使暴露評估不僅只考慮到暴露劑量，並進一步可提供強力確鑿資料數據集(dataset)以協助確認暴露來源、驗證製程改善結果與決定設備改善優先順序的暴露評估強大資料收集模式，此種方法尤其對於移動或四處奔波走動的勞工暴露評估調查特別合適。 本研究的目的是發展以主動式無線射頻辨識(active Radio Frequency Identification, active RFID)技術為基礎的自動化任務本位暴露監測系統—無線射頻識別暴露監測系統(Radio Frequency Identification Exposure Monitoring System, RFEMS)，作為室內工作場所暴露評估研究對勞工追蹤與確認的監測策略；該系統除能監測勞工時間活動模式外，還可搭配環境偵測儀器同步顯示環境感測數據，並將勞工位置及暴露資料數據即時傳回資料分析軟體以圖形介面顯示及進行資料分析。RFEMS可提供適當的定位範圍(每一定位區域直徑大小約6?45m)協助研究者在監測區域內區別微環境並辨識勞工的活動位置。經實場先期試驗結果，標準人工觀察法與RFEMS間的時間活動模式(Time Activity Pattern, TAP)測量誤差約為0.21?1.57%，結果一致性良好。 在暴露評估實場驗證方面，實驗以RFEMS搭配噪音計整合於研究背心中，並使勞工於工作過程全程配戴以同步監測勞工時間活動模式與噪音暴露劑量，實驗結果顯示RFEMS在TAP測量的準確度與人工觀察法的相關係數R2達0.909，平均測量誤差約為1.64%；在噪音劑量的測量上，應用RFEMS搭配噪音計可發展出準噪音劑量(Semi Noise Dosimetry, SND)、即時音壓電子活動紀錄間接噪音劑量(Realtime Electronic Recording Indirect Noise Dosimetry REIND)與均能音壓電子活動紀錄間接噪音劑量(Equivalent Electronic Recording Indirect Noise Dosimetry, EEIND)三種噪音劑量測量方法，測量結果與個人噪音劑量(Personal Noise Dosimetry, PND)比較，相關係數R2分別可達0.915、0.779及0.873；測量誤差以時量平均音壓級(Time Weight Average, TWA)表示分別為0.81、1.57與1.23dBA，均在噪音計的測量誤差範圍內。 綜合上述驗證結果顯示，本研究研發的RFEMS應用於室內作業場所進行自動化任務本位暴露評估監測(Automated Task-Based Exposure Assessment Monitoring, AT-BEAM)，其定位準確度確可提供作為量化時間活動模式的工具；且搭配噪音計作為環境監測儀器進行暴露評估監測結果，RFEMS可升級低階噪音計(sound level meter, SLM)使具有高階噪音劑量計(Noise Dosimeter, ND)的性能，並取得相近的噪音暴露劑量值。使用EFEMS進行勞工暴露評估監測研究，除能同步監測勞工時間活動模式，提供勞工時間活動來源進階解析外，並可節省大量研究人力與經費，對於需進一步闡釋暴露來源或進行長期暴露監測的室內暴露評估監測工作，可提供另一種有利於減少研究人力及協助長期自動追蹤暴露過程的監測策略與工具。 The exposure occurs when a person comes into contact with a pollutant at a particulate instant of time if the pollutant and the person are present at the same location. The exposure becomes the intersection, or joint occurrence, of two events: the person is present, and the pollutant is present as well. Hence, the exposure assessment depends on a complete record of the duration of exposure to assist in tracking the exposure source. The Task-Based Exposure Assessment Model (T-BEAM) stresses the identification of all hazards that may be associated with a particular work task. The Task-Based Exposure Assessment is a very powerful tool to collect data that can be utilized not only for exposure dose inclusion but also for source identification, validation of process improvements, determining retrofit control priorities and providing a strong supported dataset. This approach is be especially suitable for mobile or itinerant workers. The purpose of this study is to development an Auto Task-Based Exposure Assessment monitoring strategy based on an active radio frequency identification (active RFID) technology suitable for tracking and identifying workers’ locations in indoor workplaces. Called radio frequency identification exposure monitoring system (RFEMS), the system could also synchronously indicate the surrounding conditions using various sensors. Location and exposure data were transferred to data analysis software for visualization and tabular analysis in real-time. The RFEMS instruments provided adequate range for locating (typically ca. 6–45 m in each zone), allowing us to locate subjects within distinct microenvironments and to distinguish between the activities of a variety of workers, the average time activity pattern (TAP) recording deviation for both human observations and RFEMS was ca. 0.21–1.57%. A pilot field test indicated that the RFEMS offers a new level of accuracy for direct quantification of time activity patterns in exposure assessments of indoor workers over long periods of time. Additionally, in the field study, The RFEMS and sound level meter are mounted on the vests of workers to carry out on-site field test by monitoring the time activity pattern (TAP), and the noise dose level exposed by the workers. The results obtained using these three devices are well correlated with the results monitored by using a PND (personal noise dosimetry) with correlation coefficients (R2) of 0.915, 0.779 and 0.873, respectively. The errors of noise dose expressed in TWA (time weight average) for these three methods are 0.81, 1.57 and 1.23 dBA, respectively; they are well within the general errors of the average dosimetries. These observations indicate that the RFEMS developed in this research is applicable for conducting tasked-based measurements of indoor noise. The findings will assist in studying the source of long-term exposed by workers, and hence this devise is a valuable exposure monitoring strategy for tracing and automatic monitoring long-term exposure with reduced manpower requirement. |
