雷射杜卜勒流量計於水體污染評估之應用： 基於光學散射與流體動力學模型之整合分析

Abstract

隨著全球塑膠污染問題日益嚴重，微塑粒(Microplastics)的檢測與量化已成為環境科學與水質監測領域的核心議題。其不僅對水體生態系統造成深遠影響，亦對人類健康構成潛在風險，因此發展高精度監測技術以評估其污染程度至關重要。本研究結合雷射杜卜勒流量計(Laser Doppler Flowmeter, LDF)、光學散射模型(Optical Scattering Model)與流體力學模型(Fluid Dynamics Model)，評估水體中微塑粒污染嚴重程度，並探討 LDF 在不同粒徑組成、濃度與通量條件下之適用性與解析能力。 本研究採用混和粒徑 1~4 µm及不同濃度微塑粒進行連續流場模擬實驗，透過 LDF 精確測量水體微塑粒灌流濃度，並將該訊號作為污染評估指標。基於光學散射理論分析 LDF 訊號如何受到微塑粒粒徑分佈、折射率與濃度變化影響，同時透過流體力學模型推導微塑粒運動行為，以確保測量結果的物理合理性。且在數據處理上進一步整合濾波技術與連續小波轉換(Continuous Wavelet Transform, CWT)進行訊號處理，成功提取關鍵特徵，增強數據穩定性並提升污染監測精度。 研究結果顯示，LDF 訊號與微塑粒水溶液濃度呈顯著正相關，當濃度自 5 µg/L 增加至 1000 µg/L，LDF 訊號穩定增強。未知濃度測量的擬合曲線分析(Curve Fitting Analysis)顯示其相關係數 R² = 0.92，證實 LDF 在不同污染濃度條件下均可提供穩定且準確的評估。此外，LDF 技術展現高度靈活性，適用於淡水、海水及不同污染程度水體，為未來低成本、高效率水質監測提供可行解決方案。 本研究不僅提出 LDF 在微塑粒水污染監測之新應用，更結合光學散射理論與流體力學模型，提升測量物理合理性與解析度，為環保政策制定及後續研究提供關鍵科學依據，以促進微塑粒污染防治與永續水資源管理。

With the escalating global plastic pollution crisis, the detection and quantification of microplastics have become central issues in environmental science and water quality monitoring. Microplastics pose significant threats to aquatic ecosystems and human health, making the development of high-precision monitoring technologies essential for assessing pollution severity. This study integrates Laser Doppler Flowmetry(LDF), Optical Scattering Models, and Fluid Dynamics Models to evaluate the severity of microplastic contamination in water bodies. It investigates the applicability and resolution of LDF under varying particle size distributions, concentrations, and flow conditions. A controlled experimental setup was established using mixed microplastic particle sizes 1~4 µm and varying concentrations to simulate continuous flow conditions. LDF was utilized to quantify microplastic perfusion concentration, providing a robust indicator for pollution assessment. Optical scattering theory was applied to evaluate the effects of particle size distribution, refractive index, and concentration variations on LDF signals, while fluid dynamics modeling characterized microplastic transport behavior to ensure measurement validity. Advanced signal processing techniques, including filtering algorithms and Continuous Wavelet Transform(CWT), were implemented to extract key spectral features, enhance data stability, and refine pollution monitoring precision. The experimental results demonstrate a strong positive correlation between LDF signals and microplastic concentration in aqueous solutions. As the concentration increased from 5 µg/L to 1000 µg/L, the LDF signal exhibited a stable and significant enhancement. Further curve fitting analysis of unknown concentration measurements revealed a correlation coefficient of R^2=0.92, confirming the ability of LDF to provide consistent and accurate pollution assessments across different concentration levels. Moreover, LDF technology exhibits high flexibility and adaptability, making it suitable for application in freshwater, seawater, and various pollution levels, thus presenting a feasible and cost-effective solution for high-efficiency water quality monitoring. This study not only proposes a novel application of LDF in microplastic pollution monitoring but also integrates optical scattering models and fluid dynamics theories to enhance the physical validity and resolution of LDF measurements. The findings provide critical scientific evidence for environmental policy development and future research, contributing to microplastic pollution mitigation and sustainable water resource management.