地球科学进展 ›› 2019, Vol. 34 ›› Issue (1): 72 -83. doi: 10.11867/j.issn.1001-8166.2019.01.0072

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海洋微塑料输运的数值模拟研究进展
张晨 1( ),王清 2, *( ),赵建民 1, 2   
  1. 1. 中国科学院烟台海岸带研究所牟平海岸带环境综合试验站,山东 烟台 264003
    2. 中国科学院烟台海岸带研究所海岸带生物资源高效利用研究与发展中心,山东 烟台 264003
  • 收稿日期:2018-09-25 修回日期:2018-12-15 出版日期:2019-01-10
  • 通讯作者: 王清 E-mail:chenzhang@yic.ac.cn;qingwang@yic.ac.cn
  • 基金资助:
    国家自然科学基金面上项目“莱州湾塑料微粒(microplastics)的污染现状及其毒性效应研究”(编号: 41576122);中国科学院青年创新促进会(编号:2016196)

Numerical Simulation of Transportation of Marine Microplastics A Review

Chen Zhang 1( ),Qing Wang 2, *( ),Jianmin Zhao 1, 2   

  1. 1. Muping Coastal Environment Research Station, Yantai Institute of Coastal Zone Research Chinese Academy of Sciences, Shandong Yantai 264003, China
    2. Research and Development Center for Efficient Utilization of Coastal Bioresources, Yantai Institute of Coastal Zone Research Chinese Academy of Sciences, Shandong Yantai 264003, China
  • Received:2018-09-25 Revised:2018-12-15 Online:2019-01-10 Published:2019-03-05
  • Contact: Qing Wang E-mail:chenzhang@yic.ac.cn;qingwang@yic.ac.cn
  • About author:Zhang Chen(1984-), male, Laiyang City, Shandong Province, Engineer. Research areas include Physical Oceanography. E-mail: chenzhang@yic.ac.cn |Wang Qing(1981-), male, Jining City, Shandong Provine, Associate professor. Research areas include marine ecology. E-mail: qingwang@yic.ac.cn
  • Supported by:
    Project supported by the National Natural Science Foundation of China “Study on the pollution status and toxic effects of microplastic in Laizhou Bay”(No. 41576122);Youth Innovation Promotion Association(No. 2016196)

微塑料采样数据在时间、空间上的不连续性限制了对微塑料源、汇区域、传输途径及发展趋势的研究。采用现场调查与数值模拟相结合的方法,能够综合研究微塑料自身特征、气象及水动力环境因素对微塑料分布和输运的影响。主要从微塑料输运的数值模拟方法、模拟研究及应用方面综述微塑料模拟研究进展,可归纳为:微塑料输运模型主要驱动场(流场)的构建;风、海浪、地形和极端海况等环境因素对不同(粒径、密度和形状)微塑料粒子性质和输运过程的影响;数值模拟工具在微塑料清除研究中的应用。同时基于近年来数值模拟方法在微塑料研究中的应用,展望未来该领域需要关注的研究方向,包括结合实测数据和输运模型,研究微塑料的分布特征及演变规律;微塑料输运的相关参数(粗糙度、风拖曳系数、沉降速率和再悬浮速率和污损率等)对气象和水动力影响响应的模拟研究,相应的敏感性模拟实验结果需要与采样调查和实验室检测结果对比验证,以改进数值模型的经验参数和公式。

The temporal and spatial discontinuity of microplastic sampling data restricts the investigation on their source, sink, transport pathway and trend. Numerical simulation combined with sampling investigation can comprehensively study the effects of microplastic characteristics, meteorology and hydrodynamics on the distribution and transportation of microplastics. In this paper, the studies of microplastic numerical simulation were reviewed from the aspects of numerical simulating research and their applications in microplastic tranportation, and the results were summarized as follows: The construction of the main driving force (current); the influence of environmental factors, such as wind, waves, topography and extreme sea conditions on the properties of microplastics with different characteristics (particle size, density, shape) and their tranportation; the application of numerical simulation in the study of microplastic removal. Based on progress on the study of numerical simulation of marine microplastics, the future directions were pointed out that the further simulating studies should focuson the spatio-temporal distribution and evolvement of microplastics by combining sampling data and numerical model, the simulating research on the relationship between microplastic parameters (roughness, wind drag coefficient, settling rate, resuspension rate and biofouling rate) and (meteorological and ocean) dynamic condition. Moreover, the results of simulating sensitivity experiments should be compared with sampling and laboratory testing data to improve the empirical parameters and formulas of numerical model.

中图分类号: 

表1 可获取的海洋再分析资料、动力学模型、粒子运动轨迹数据和 PTM模型 [ 51 ]
Table 1 Available ocean reanalysis data, dynamic model, particle trajectory data and PTM model [ 51 ]
数据库/数值模型 数据库/数值模型描述
BLUELink 澳大利亚联邦科学与工业研究组织CSIRO提供的海况精确预报和分析模型[ 52 ]
Connie2/ Connie3 由CSIRO开发并共享的海水中粒子运动轨迹的可视化工具[ 53 ]
ECCO1/ECCO2 海洋环流与气候评估数据库,由美国国家航空航天局(NASA)喷气推进实验室(JPL)和麻省理工学院(MIT)构建的集合卫星数据和原位观测海洋数据的多源海洋数据系统[ 54 ]
ECMWF ORA-S3 欧洲中尺度天气预报中心ECMWF海洋再分析数据[ 54 ]
Global drifter program 美国国家海洋和大气管理局(NOAA)提供的卫星追踪海表漂流浮标数据[ 53 , 55 ]
GNOME NOAA提供的可控环境模型,用于模拟海洋中污染粒子的运动轨迹[ 56 ]
HYCOM 由美国海军全球大气预报系统(NOGAP)驱动的混合坐标模型HYCOM[ 57 , 58 ]
NCOM 美国海军海洋局(NAVOCEANO)提供的全球实时海洋数据(分辨率为1/8°),由海军近岸模型NCOM驱动[ 54 ]
NEMO 欧洲海洋模型NEMO[ 59 ]
NLOM 美国海军海洋局(NAVOCEANO)提供的全球实时海洋数据(分辨率为1/32°),由海军层化模型NLOM驱动[ 54 ]
OSCAR 由NOAA提供的海表流场再分析实时数据[ 60 ]
OSCURS 由NOAA提供的海洋流场模型[ 61 , 62 ]
PELET-2D 二维拉格朗日粒子追踪模型[ 63 ]
plasticadrift.org Sebille等由全球海表漂流浮标信息反演的表层漂浮碎屑运动轨迹数据[ 64 , 65 ]
Pol3DD 拉格朗日三维数值扩散模型[ 57 , 58 ]
SCUD 国际太平洋研究中心IPRC研发的表面海流诊断工具[ 44 , 45 ]
SODA 由美国国家大气研究中心开发的简单海洋再分析数据库[ 54 , 66 ]
表2 鉴定样品聚合物种类、密度和数量 [ 78 ]
Table 2 Types, densities and quantities of identified polymer samples [ 78 ]
表3 微塑料输运的影响因素
Table 3 Influencing factors of transport of microplastics
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