暴露濃度推估模式為評估作業環境健康風險之重要工具，特別是在量測資料不足或現場採樣受限的情況下，可用以估算污染物之實際暴露水準。其中，近場－遠場（Near-field/Far-field, NF/FF）模式適用於缺乏明顯氣流且以擴散為主的室內環境，能有效描述近場與遠場之間的濃度差異。然而，既有研究多侷限於單一污染源情境，且普遍假設污染物產生率（Generation rate, G）為固定且已知，同時忽略非通風移除機制所造成之隱性損失（sink loss, ksink），使得 NF/FF 模式於實際作業場所中的適用性受到限制。
本研究針對上述限制，於一模擬室內場域（體積為 221 m³ 之教室）中，建立單一與雙重揮發性有機化合物（Volatile Organic Compounds, VOCs）污染源之暴露濃度推估模式。以相對低毒性之異丙醇（Isopropyl alcohol, IPA）作為目標污染物，透過蠕動泵浦控制其逸散速率，並於三種空氣交換率條件（Air change per hour, ACH = 1、2、3）下進行實驗。研究中於近場配置兩台、遠場配置一台光離子化偵測器（Photoionization Detector, PID），同步量測 IPA 濃度，各通風條件皆重複進行三次試驗。近遠場交換風量（β）依文獻設定為 0.054 m³/s，以降低通風變動對模式參數之影響。
模式係依質量平衡原理建立，並以 Runge–Kutta 法進行離散化，結合 Excel 規劃求解功能之最小平方和法擬合模式與實測濃度曲線， G與ksink，並透過解析解計算任意時間點濃度作為模式驗證依據。研究結果顯示，單一污染源情境下 G 之推估誤差為 −1.6% 至 −0.3%；雙污染源且逸散速率相近時，誤差進一步降低至 −1.5% 至 −0.4%。當雙源逸散速率差異較大時，強源仍維持低誤差，而弱源誤差相對提高。所有情境中反推之 ksink 均趨近於零，顯示 IPA 之濃度衰減主要受通風控制。整體而言，本研究證實 NF/FF 模式可於實場情境中準確反推雙污染源逸散速率，具備作為室內多源 VOC 暴露評估工具之實務應用價值。

Exposure concentration estimation models are critical tools for evaluating occupational health risks, particularly when measurement data are limited or on-site sampling is constrained. The Near-Field/Far-Field (NF/FF) model is well suited for indoor environments dominated by diffusive transport, as it can describe concentration differences between near-field and far-field zones. However, previous applications have largely been limited to single-source scenarios, often assuming known and constant generation rates (G) and neglecting non-ventilation removal mechanisms (ksink), thereby limiting applicability in real workplaces.
In this study, NF/FF exposure models were developed for single and dual volatile organic compound (VOC) sources in a simulated classroom environment (221 m³). Isopropyl alcohol (IPA) was selected as the target VOC, with emission rates controlled by a peristaltic pump. Experiments were conducted under three ventilation conditions (ACH = 1, 2, and 3). IPA concentrations were synchronously measured using photoionization detectors deployed in near-field and far-field zones. Model parameters were estimated by fitting discretized mass-balance equations, solved using the Runge–Kutta method, to measured concentrations via least-squares optimization, allowing back-calculation of G and ksink.
Estimated G errors ranged from −1.6% to −0.3% for single-source scenarios and decreased to −1.5% to −0.4% for dual-source scenarios with similar emission rates. When emission rates differed substantially, errors remained low for the stronger source but increased for the weaker source. Estimated ksink values approached zero across all scenarios. Model prediction performance was stable, with near-field RMSEs of approximately 4–5 ppm and far-field RMSEs of 2–3 ppm. These results demonstrate that the NF/FF model can accurately estimate emission rates for dual-source indoor VOC scenarios and serves as a practical tool for multi-source exposure assessment.

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