本研究利用拉格朗日粒子追踪演算法來表示海洋塑料碎片（PMD）的傳輸，發現
台灣海峽的季節變化傳輸相互對應。預計可能軌跡的結果可用於推估源處的PMD 量。
首先，透過模擬216 個質點平均值並使用TORI（台灣海洋科技研究所）高頻（HF）岸
基雷達測流系統所監測之海流資料(2015-2017)，可以推測PMD 可能的來源。因澎湖群
島位於台灣海峽中部，因此被選為PMD目的地。
首次結果是由波浪運動引起的海洋混合和斯托克斯漂流是應用高頻雷達模擬PMD
軌跡的不確定性因素。採用頻散係數（K）來表示水平混合效率。利用2015-2017 年模
擬結果，K 的平均大小在春季為1.06 × 10−4，夏季為3.66 × 10−5，秋季為2.13 × 10−4，
冬季為1.87 × 10−4。這表示地面風速在PMD 傳輸中的重要性，高頻雷達數據能夠顯現
出這些現象。根據數據結果，使用高頻雷達的模擬結果可以求得誤差。因高頻雷達的
數據存在不確定性，造成每個PMD 軌跡不準確，因此我們從機率角度採用係集平均結
果表示PMD軌跡。2015-2017 年模擬結果，PMD傳輸模式的百分比是東海（I 區）4.27
％，中國大陸沿岸（區域II）3.72％，南海（區域III）19.38％，台灣SW（區域IV）
17.88％，台灣西（區域V）48.87％，台灣西北（區域VI）5.86％。台灣西（V 區）在
澎湖群島生產PMD 的可能性較高，尤其是雲林海岸。通過冬季的中國沿岸流（CCC）
導致的區域I（來自東海，冬季機率較高）和III（來自南中國海，夏季機率較高）之間
的機率，可以確定顯著的季節性偏差。夏季北上台灣暖流（TWC）。
結果的第二部分是PMD 數量的計算。只有在來源處的PMD 資訊已知時才能使用
這些軌跡。可以透過PMD 來源總數乘以對應機率來計算數量。利用Jambeck 方法
（2015）以及每月河流排放，計算出從河流中流入海洋的PMD 量。澎湖群島的PMD
季節變化，可以透過長江（進入東海），湄公河（進入南海）和彭亨河（進入南海）
的河流流量計算。結果表示，長江夏季東海海域PMD 最高，而湄公河和彭亨河秋季
PMD最高。較高的PMD 是由較高的河流流量引起的，受季風期間降雨模式的影響。

In the study of Taiwan Strait, a lagrangian particle tracking algorithms were applied to
characterize the transport of Plastic Marine Debris (PMD) which correspond to the seasonal
variability transportation in Taiwan Strait. The results of estimation probable trajectories could
be used to estimate the PMD amount at the sources. First, the estimation of PMD possible
sources could be obtained by simulating an ensemble average over 216 floating elements and
using the remote sensing surface ocean current data provided by TORI (Taiwan Ocean Research
Institute) High Frequency (HF) coastal radar network from 2015-2017. The Penghu Islands
were located in the middle of Taiwan Strait were chosen as PMD destination for example.
The results of first discussion are, ocean mixing and stokes drift that induced by wave
motion, were the main factors in uncertainty of applying HF coastal radar to simulate PMD
trajectories. The Dispersion Coefficient (K) was adopted to represent the horizontal mixing
efficiency. Based on the simulation results over 3 years, the average magnitude of K revealed
1.06 × 10−4 in spring, 3.66 × 10−5 in summer, 2.13 × 10−4 in fall, and 1.87 × 10−4 winter.
The periodic oscillation of dispersion coefficients could be identified, with an average period
of 4 days. It denoted that the surface wind speed plays important role in the PMD transport and
the HF data is capable to reflect these phenomena. Based on data, the simulation result error
using HR radar was known. The uncertainty of HF radar data for each PMD trajectories might
inaccurate, so we used probability viewpoint based on the results of ensemble average. Based
on simulation results for three years, the percentage of PMD transport patterns was East China
Sea (region I) 4.27%, Cross-Strait Mainland China (region II) 3.72%, South China Sea (region
III) 19.38%, Taiwan SW (region IV) 17.88%, Taiwan West (region V) 48.87%, and Taiwan
NW (region VI) 5.86%. Taiwan West (region V) has a higher possibility to produce PMD in
Penghu Islands, especially Yunlin Coast. The significant seasonal bias could be identified by
comparing the probability between region I (from East China Sea, higher probability in winter)
and III (from South China Sea, high probability in summer) due to prevailing southward China
Coastal Current (CCC) in winter and northward Taiwan Warm Current (TWC) in summer.
The second part of the results is the calculation of PMD amount. These trajectories
information could only be used if the PMD at source point was known already. The amount
could be calculated by multiplying the probability with the total amount of PMD at the sources.
ii
Monthly river discharge was applied to find the amount of PMD released from riverine using
Jambeck’s method (2015). PMD seasonal variability in the Penghu Islands were calculated
based on Yangtze River (into East China Sea), Mekong River (into South China Sea), and
Pahang River (into South China Sea). The results showed that Yangtze river produced the
highest PMD during summer to East China Sea, while Mekong and Pahang River released the
highest PMD during fall. This higher PMD was induced by higher riverine discharge which
was influenced by rainfall pattern during monsoon.

ABSTRACT .i
摘要.iii
ACKNOWLEDGMENTiv
TABLE OF CONTENTS v
LIST OF TABLESvii
LIST OF FIGURESviii
CHAPTER I INTRODUCTION 1
1.1 Motivation.. 1
1.2 Literature Review .. 2
1.2.1 Introduction of Plastic Marine Debris.. 2
1.2.2 Distribution of Plastic Marine Debris 4
1.2.3 Estimation of Plastic Marine Debris Amount .. 5
1.2.4 Relation Between Rainfall and the Amount of Plastic Marine Debris. 7
1.2.5 Ocean Current Circulation in Taiwan Strait.. 9
1.2.6 Calculation of Plastic Marine Debris Transportation. 11
1.2.7 Dispersion of Trajectories 11
1.2.8 Observation of Stokes Drift. 12
1.3 The Producing of Plastic Marine Debris in Some Countries. 13
1.3.1 Plastic Marine Debris in Mainland China 13
1.3.2 Plastic Marine Debris in Indonesia.. 13
1.3.3 Plastic Marine Debris in Vietnam 14
1.3.4 Plastic Marine Debris in France 14
1.4 Scope of Present Study . 15
CHAPTER II RESEARCH METHODOLOGY .. 16
2.1 Study Area .. 16
2.2 Data Collection . 16
2.2.1 High Frequency (HF) coastal radar . 16
2.2.2 Sea Surface Temperature (SST) 22
2.2.3 Ocean Wind . 23
2.3 Estimation of Mismanaged Plastic Waste (MMPW) in the River.. 23
2.4 Backward Track Simulation .. 24
2.4.1 Simulation Design 24
2.4.2 Classification of Possible Source . 28
2.5 Sampling Method. 29
2.6 Data Processing 29
2.6.1 Trajectories Simulation.. 29
2.6.2 Calculation of Dispersion Coefficient in Taiwan Strait 34
CHAPTER III RESULT AND DISCUSSION 35
3.1 Application HF Coastal Radar in Trajectories Simulation . 35
3.1.1 Trajectories Prediction Using HF Radar Surface Currents: Monte Carlo
Simulations of Prediction Uncertainties (Ulman et al., 2006) .. 37
3.1.2 Application of High Frequency Radar in Hazard Management (Mal Heron et
al., 2016) 38
3.1.3 Eularian and Lagrangian Correspondence of HF Radar and Surface Drifter
Data (I. I. Rypina et al., 2014).. 39
3.2 Dispersion of Trajectories Simulation in Taiwan Strait .. 39
3.2.1 Dispersion Coefficient in Taiwan Strait 41
3.2.2 Map of Dispersion Coefficient in Taiwan Strait .. 58
3.3 Seasonal Variability of Possible Source Plastic Marine Debris.. 63
3.4 Validation Simulation Result and Beach Clean Up Data 69
3.5 Monthly Mismanaged Plastic Waste from the River. 72
3.4.1 Yangtze River. 72
3.4.2 Mekong River. 75
3.4.3 Pahang River .. 78
CHAPTER IV CONCLUSIONS. 83
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APPENDIX A – SIMULATION RESULT .. 90
APPENDIX B – DISPERSION COEFFICIENT 170
APPENDIX C – AUTOCORRELATION.. 191
APPENDIX D – BEACH CLEAN UP DATA.. 211T

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